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apps.yaml settings

+

The basic configuration for Predbat is configured in the apps.yaml file.

+

Depending on whether you have used the combined AppDaemon/Predbat add-on installation method or the +HACS, Appdaemon add-on then Predbat installation method, the apps.yaml file will be held in one of two directories in Home Assistant:

+
    +
  • /addon_configs/46f69597_appdaemon-predbat/apps if you used the combined AppDaemon/Predbat add-on installation method
  • +
+

or

+
    +
  • /config/appdaemon/apps/batpred/config/ if you used the HACS, AppDaemon add-on then Predbat installation method
  • +
+

You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) +to edit the apps.yaml file - see editing configuration files within Home Assistant if you need to install an editor.

+

This section of the documentation describes what the different configuration items in apps.yaml do.

+

When you edit apps.yaml, AppDaemon will automatically detect the change and Predbat will be reloaded with the updated file. +You don't need to restart the AppDaemon add-on for your edits to take effect.

+

Templates

+

You can find template configurations in the following locations:

+ + + + + + + + + + + + + + + + + + + + + +
TemplateLink
GivEnergyapps.yaml
SolisXapps.yaml
SolarEdgeapps.yaml
+

The GivEnergy template will be installed by default but if you are using another inverter please copy the correct template into the directory +where your apps.yaml is stored, and modify it from there.

+

Basics

+

Basic configuration items

+
    +
  • +

    prefix - Set to the prefix name to be used for all entities that predbat creates in Home Assistant. Default 'predbat'. Unlikely that you will need to change this.

    +
  • +
  • +

    timezone - Set to your local timezone, default is Europe/London. It must be set to a +valid Python time zone for your location

    +
  • +
  • +

    template - Initially set to True, this is used to stop Predbat from operating until you have finished configuring your apps.yaml. +Once you have made all other required changes to apps.yaml this line should be deleted or commented out.

    +
  • +
  • +

    notify_devices - A list of device names to notify when Predbat sends a notification. The default is just 'notify' which contacts all mobile devices

    +
  • +
  • +

    days_previous - A list (one entry per line) of the number of days of historical house load to be used to predict your future daily load.
    +It's recommended that you set days_previous so Predbat uses sufficient days' history so that 'unusual' load activity (e.g. saving sessions, "big washing day", etc) get averaged out.
    +Typical settings could be 1, 7 or 7, 14, or 2, 3, 4, 5, 6, 7, 8.
    +Do keep in mind that Home Assistant only keeps 10 days history by default, so you might need to increase the number of days history kept in HA before its purged +by editing and adding the following to the /homeassistant/configuration.yaml configuration file and restarting Home Assistant afterwards:

    +
  • +
+
    recorder:
+      purge_keep_days: 14
+
+
    +
  • +

    days_previous_weight - A list (one entry per line) of weightings to be applied to each of the days in days_previous. Default value is 1, that all history days are equally weighted.

    +
  • +
  • +

    forecast_hours - the number of hours to that Predbat will forecast ahead, 48 is the suggested amount, although other values can be used +such as 30 or 36 if you have a small battery and thus don't need to forecast 2 days ahead.

    +
  • +
+

Inverter information

+

The template apps.yaml comes pre-configured with regular expressions that should auto-discover the GivTCP Home Assistant entity names. +If you have more than one inverter or entity names are non-standard then you will need to edit apps.yaml for your inverter entities. +For other inverter brands, see Other Inverters

+
    +
  • +

    num_inverters - The number of inverters you have. If you increase this above 1 you must provide multiple of each of the inverter entities

    +
  • +
  • +

    geserial - This is a helper regular expression to find your serial number, if it doesn't work edit it manually or change individual entities to match.

    +
  • +
+

Historical data

+

Predbat can either get historical data (house load, import, export and PV generation) directly from GivTCP or it can obtain it from the GivEnergy cloud. +Unless you have a specific reason to not use the GivTCP data (e.g. you've lost your GivTCP data), its recommended to use GivTCP.

+

Data from GivTCP

+

The following configuration entries in apps.yaml are pre-configured to automatically use the appropriate GivTCP sensors.

+

If you have a 3-phase electricity supply and one inverter (and battery) on each phase then you will need to add one line for the load, import, export and PV sensors +for each of the 3 phases.

+

If you have a single phase electricity supply and multiple inverters on the phase then you will need to add one line for each of the load and PV sensors. +You don't need multiple lines for the import or export sensors as each inverter will give the total import or export information.

+

Edit if necessary if you have non-standard GivTCP sensor names:

+
    +
  • load_today - GivTCP Entity name for the house load in kWh today (must be incrementing)
  • +
  • import_today - GivTCP Imported energy today in kWh (incrementing)
  • +
  • export_today - GivTCP Exported energy today in kWh (incrementing)
  • +
  • pv_today - GivTCP PV energy today in kWh (incrementing). If you have multiple inverters, enter each inverter PV sensor on a separate line.
    +If you have an AC-coupled GivEnergy inverter then enter the Home Assistant sensor for your PV inverter.
    +If you don't have any PV panels, comment or delete this line out of apps.yaml.
  • +
+

See the Workarounds section below for configuration settings for scaling these if required.

+

If you have multiple inverters then you may find that the load_today figures from GivTCP are incorrect as the inverters share the house load between them. +In this circumstance one solution is to create a Home Assistant template helper to calculate house load from {pv generation}+{battery discharge}-{battery charge}+{import}-{export}.

+

e.g.

+
{{ states('sensor.givtcp_XXX_pv_energy_today_kwh')|float(0) + <inverter 2>...
++ states('sensor.givtcp_XXX_battery_discharge_energy_today_kwh')|float(0) + <inverter 2>...
+- states('sensor.givtcp_XXX_battery_charge_energy_today_kwh')|float(0) - <inverter 2>...
++ states('sensor.givtcp_XXX_import_energy_today_kwh')|float(0)
+- states('sensor.givtcp_XXX_export_energy_today_kwh')|float(0) }}
+
+

GivEnergy Cloud Data

+

If you have an issue with the GivTCP data, Predbat can get the required historical data from the GivEnergy cloud instead. This data is updated every 30 minutes. +Obviously connecting to the cloud is less efficient and means that Predbat will be dependent upon your internet connection and the GivEnergy cloud to operate.

+
    +
  • ge_cloud_data - When True Predbat will use the GE Cloud for data rather than load_today, import_today and export_today
  • +
  • ge_cloud_serial - Set the inverter serial number to use for the Cloud data
  • +
  • ge_cloud_key - Set to your API Key for the GE Cloud (long string)
  • +
+

Load filtering

+

By default if Predbat sees a gap in the historical load data it will fill it with average data. This is to help in the cases of small amounts of lost data. +For entire lost days you should change days_previous to point to different days(s) or include 3 or more days and if you set switch.predbat_load_filter_modal to true, +the lowest day's historical load will be discarded.

+
    +
  • load_filter_threshold - Sets the number of minutes of zero load data to be considered a gap (that's filled with average data), the default is 30. +To disable, set it to 1440.
  • +
+

Inverter control configurations

+
    +
  • +

    inverter_limit - One per inverter. When set defines the maximum watts of AC output power for your inverter (e.g. 3600). +This will help to emulate clipping when your solar produces more than the inverter can handle, but it won't be that accurate as the source of the data isn't minute by minute. +If you have a separate Solar inverter as well then add the solar inverter limit to the battery inverter limit to give one total amount.

    +
  • +
  • +

    export_limit - One per inverter (optional). When set defines the maximum watts of AC power your inverter can export to the grid at (e.g. 2500). +This will emulate the software export limit setting in the Inverter that you will have if your G98/G99 +approval was lower than your maximum inverter power (check your install information for details). +If you do not set an export limit then it's the same as the inverter limit.

    +
  • +
  • +

    inverter_limit_charge and inverter_limit_discharge - One per inverter (optional). When set in watts, overrides the maximum +charge/discharge rate settings used when controlling the inverter. +This can be used if you need to cap your inverter battery rate (e.g. charge overnight at a slower rate to reduce inverter/battery heating) as Predbat +will normally configure all timed charges or discharges to be at the inverter's maximum rate.

    +
  • +
+

Controlling the Inverter

+

There are two ways that Predbat can control GivTCP to control the inverter, either via REST API calls (preferred) or via the GivTCP inverter controls in Home Assistant.

+

REST Interface inverter control

+
    +
  • givtcp_rest - One per Inverter, sets the GivTCP REST API URL (http://homeassistant.local:6345 +is the normal one for the first inverter and :6346 for the second inverter). +When enabled the Control per inverter below isn't used and instead communication from Predbat to GivTCP is directly via REST and thus bypasses some issues with MQTT. +If using Docker then change homeassistant.local to the Docker IP address.
  • +
+

To check your REST is working open up the readData API point in a Web browser e.g: http://homeassistant.local:6345/readData

+

If you get a bunch of inverter information back then it's working!

+

It's recommended you enable 'Output Raw Register Values' in GivTCP (via Settings / Add-on's / GivTCP / configuration tab) for added monitoring:

+

image

+

Home Assistant inverter control

+

As an alternative to REST control, Predbat can control the GivEnergy inverters via GivTCP controls in Home Assistant. +The template apps.yaml is pre-configured with regular expressions for the following configuration items that should auto-discover the GivTCP controls, +but may need changing if you have multiple inverters or non-standard GivTCP entity names.

+

The givtcp_rest line should be commented out/deleted in order for Predbat to use the direct GivTCP Home Assistant controls.

+
    +
  • charge_rate - GivTCP battery charge rate entity in watts
  • +
  • discharge_rate - GivTCP battery discharge max rate entity in watts
  • +
  • battery_power - GivTCP current battery power in watts
  • +
  • pv_power - GivTCP current PV power in watts
  • +
  • load_power - GivTCP current load power in watts
  • +
  • soc_kw - GivTCP Entity name of the battery SOC in kWh, should be the inverter one not an individual battery
  • +
  • soc_max - GivTCP Entity name for the maximum charge level for the battery
  • +
  • reserve - GivTCP sensor name for the reserve setting in %
  • +
  • inverter_mode - GivTCP inverter mode control
  • +
  • inverter_time - GivTCP inverter timestamp
  • +
  • charge_start_time - GivTCP battery charge start time entity
  • +
  • charge_end_time - GivTCP battery charge end time entity
  • +
  • charge_limit - GivTCP Entity name for used to set the SOC target for the battery in percentage
  • +
  • scheduled_charge_enable - GivTCP Scheduled charge enable config
  • +
  • scheduled_discharge_enable - GivTCP Scheduled discharge enable config
  • +
  • discharge_start_time - GivTCP scheduled discharge slot_1 start time
  • +
  • discharge_end_time - GivTCP scheduled discharge slot_1 end time
  • +
+

If you are using REST control the above GivTCP configuration items can be deleted or commented out of apps.yaml.

+

Solcast Solar Forecast

+

As described in the Predbat installation instructions, Predbat needs a solar forecast +in order to predict solar generation and battery charging which can be provided by the Solcast integration.

+

The template apps.yaml is pre-configured with regular expressions for the following configuration items that should auto-discover the Solcast entity names. +They are unlikely to need changing although a few people have reported their entity names don't contain 'solcast' so worth checking, or edit if you have non-standard names:

+
    +
  • pv_forecast_today - Entity name for today's Solcast forecast
  • +
  • pv_forecast_tomorrow - Entity name for tomorrow's Solcast's forecast
  • +
  • pv_forecast_d3 - Entity name for Solcast's forecast for day 3
  • +
  • pv_forecast_d4 - Entity name for Solcast's forecast for day 4 (also d5, d6 & d7 are supported, but not that useful)
  • +
+

If you do not have a PV array then comment out or delete these Solcast lines from apps.yaml.

+

If you have multiple PV arrays connected to GivEnergy Hybrid inverters or you have GivEnergy AC-coupled inverters, then ensure your PV configuration in Solcast covers all arrays.

+

If however you have a mixed PV array setup with some PV that does not feed into your GivEnergy inverters +(e.g. hybrid GE inverters but a separate older FIT array that directly feeds AC into the house), +then it's recommended that Solcast is only configured for the PV connected to the GivEnergy inverters.

+

Solcast produces 3 forecasted PV estimates, the 'central' (50% or most likely to occur) PV forecast, the '10%' (worst case) PV forecast, and the '90%' (best case) PV forecast.
+By default Predbat will use the central estimate and applies to it the input_number.pv_metric10_weight weighting of the 10% (worst case) estimate.

+

Predbat models cloud coverage by using the difference between the PV and PV10 forecasts to work out a cloud factor, +this modulates the PV output predictions up and down accordingly as if there were passing clouds. +This can have an impact on planning, especially for things like freeze charging which could assume the PV will cover the house load but it might not due to clouds.

+
    +
  • pv_estimate in apps.yaml can be used to configure Predbat to always use the 10% forecast by setting the configuration item to '10', +or '90' to always use the 90% PV estimate (not recommended!).
    +Set to blank or delete / comment out the line to use the default central estimate.
  • +
+

If pv_estimate is set to 10 then input_number.pv_metric10_weight in Home Assistant should be set to 1.0.

+

Energy Rates

+

There are a number of configuration items in apps.yaml for telling Predbat what your import and export rates are.

+

These are described in detail in Energy Rates and are listed here just for completeness:

+
    +
  • metric_octopus_import - Import rates from the Octopus Energy integration
  • +
  • metric_octopus_export - Export rates from the Octopus Energy integration
  • +
  • metric_octopus_gas - Gas rates from the Octopus Energy integration
  • +
  • octopus_intelligent_slot - Octopus Intelligent GO slot sensor from the Octopus Energy integration
  • +
  • octopus_saving_session - Energy saving sessions sensor from the Octopus Energy integration
  • +
  • octopus_saving_session_octopoints_per_penny - Sets the Octopoints per pence
  • +
  • rates_import_octopus_url - Octopus pricing URL (over-rides metric_octopus_import)
  • +
  • rates_export_octopus_url - Octopus export pricing URL (over-rides metric_octopus_export)
  • +
  • metric_standing_charge - Standing charge in pounds
  • +
  • rates_import - Import rates over a 24-hour period with start and end times
  • +
  • rates_export - Export rates over a 24-hour period with start and end times
  • +
  • rates_import_override - Over-ride import rate for specific date and time range, e.g. Octopus Power-up events
  • +
  • rates_export_override - Over-ride export rate for specific date and time range
  • +
  • futurerate_url - URL of future energy market prices for Agile users
  • +
  • futurerate_adjust_import and futurerate_adjust_export - Whether tomorrow's predicted import or export prices should be adjusted based on market prices or not
  • +
  • futurerate_peak_start and futurerate_peak_end - start/end times for peak-rate adjustment
  • +
  • futurerate_peak_premium_import and futurerate_peak_premium_export - price premium to be added during the peak period
  • +
+

Car Charging Integration

+

Predbat is able to include electric vehicle charging in its plan and manage the battery activity so that the battery isn't discharged into your car when the car is charging +(although you can over-ride this if you wish by setting the switch.predbat_car_charging_from_battery to True in Home Assistant).

+

There are two different ways of planning car charging into cheap slots with Predbat, either by the Octopus Energy integration or by Predbat identifying the cheapest slots. +These approaches and the set of settings that need to be configured together are described in Car Charging Planning.

+

The full list of car charging configuration items in apps.yaml that are used to plan car charging activity within Predbat are described below. +The Home Assistant controls (switches, input numbers, selectors, etc) related to car charging are described in Car Charging configuration within Home Assistant, +with brief mention of pertinent controls included here alongside the apps.yaml configuration items where relevant for context.

+
    +
  • num_cars should be set in apps.yaml to the number of cars you want Predbat to plan for. +Set to 0 if you don't have an EV (and the remaining car sensors in apps.yaml can safely be commented out or deleted as they won't be required).
  • +
+

Car Charging Filtering

+

You might want to remove your electric car charging data from the historical house load data so as to not bias the calculations, otherwise you will get +high battery charge levels when the car was charged previously (e.g. last week).

+
    +
  • +

    switch.car_charging_hold - A Home Assistant switch that when turned on (True) tells Predbat to remove car charging data from Predbat's battery prediction plan.

    +
  • +
  • +

    car_charging_energy - Set in apps.yaml to point to a Home Assistant entity which is the incrementing kWh data for the car charger. +This has been pre-defined to a regular expression to auto-detect the appropriate Wallbox and Zappi car charger sensors, or edit as necessary in apps.yaml for your charger sensor.

    +
  • +
  • +

    input_number.car_charging_energy_scale - A Home Assistant entity used to define a scaling factor (in the range 0.1 to 1.0) +to multiply the car_charging_energy data by if required (e.g. set to 0.001 to convert Watts to kW).

    +
  • +
+

If you do not have a suitable car charging kWh sensor in Home Assistant then comment the car_charging_energy line out of apps.yaml and configure the following Home Assistant entity:

+
    +
  • input_number.car_charging_threshold - Sets the threshold above which home consumption is assumed to be car charging and will be removed from the home load data (default 6 = 6kW).
  • +
+

Planned Car Charging

+

These features allow Predbat to know when you plan to charge your car.

+

If you have Intelligent Octopus setup then planning of charging is done via the Octopus app and Predbat obtains this information through the Octopus Energy integration in Home Assistant.

+
    +
  • switch.predbat_octopus_intelligent_charging - When this Home Assistant switch is enabled, Predbat will plan charging around the Intelligent Octopus slots, taking +it into account for battery load and generating the slot information
  • +
+

The following apps.yaml configuration items are pre-defined with regular expressions to point to appropriate sensors in the Octopus Energy integration. +You should not normally need to change these if you have Octopus Intelligent:

+
    +
  • +

    octopus_intelligent_slot - Points to the Octopus Energy integration 'intelligent dispatching' sensor that indicates +whether you are within an Octopus Energy "smart charge" slot, and provides the list of future planned charging activity.

    +
  • +
  • +

    octopus_ready_time - Points to the Octopus Energy integration sensor that details when the car charging will be completed by.

    +
  • +
  • +

    octopus_charge_limit - Points to the Octopus Energy integration sensor that provides the car charging limit.

    +
  • +
+

If you don't use Intelligent Octopus then the above 3 Octopus Intelligent configuration lines in apps.yaml can be commented out or deleted, +and there are a number of other apps.yaml configuration items that should be set:

+
    +
  • +

    car_charging_planned - Optional, can be set to a Home Assistant sensor which lets Predbat know the car is plugged in and planned to charge during low rate slots. +Or manually set it to 'False' to disable this feature, or 'True' to always enable.

    +
  • +
  • +

    car_charging_planned_response - An array of values for the above car_charging_planned sensor which indicate that the car is plugged in and will charge +in the next low rate slot. Customise for your car charger sensor if it sets sensor values that are not in the pre-defined list.

    +
  • +
  • +

    car_charging_now - For some cases finding details of planned car charging is difficult to obtain (e.g. Ohme with Intelligent doesn't report slots).
    +The car_charging_now configuration item can be set to point to a Home Assistant sensor that tells you that the car is currently charging. +Predbat will then assume this 30 minute slot is used for charging regardless of the plan.
    +If Octopus Intelligent Charging is enabled and car_charging_now indicates the car is charging then Predbat will also assume that this is a +low rate slot for the car/house (and might therefore start charging the battery), otherwise electricity import rates are taken from the normal rate data.

    +
  • +
  • +

    car_charging_now_response - Set to the range of positive responses for car_charging_now to indicate that the car is charging. +Useful if you have a sensor for your car charger that isn't binary.

    +
  • +
+

To make planned car charging more accurate, configure the following items in apps.yaml:

+
    +
  • +

    car_charging_battery_size - Set to the car's battery size in kWh, defaults to 100. It will be used to predict car charging stops.

    +
  • +
  • +

    car_charging_limit - Set to point to a sensor that specifies the % limit the car is set to charge to. Default is 100%

    +
  • +
  • +

    car_charging_soc - Set to point to a sensor that specifies the car's current % charge level. Default is 0%

    +
  • +
+

Multiple Electric Cars

+

Multiple cars can be planned with Predbat, in which case you should set num_cars in apps.yaml to the number of cars you want to plan

+
    +
  • +

    car_charging_limit, car_charging_planned, car_charging_battery_size and car_charging_soc must then be a list of values (i.e. 2 entries for 2 cars)

    +
  • +
  • +

    If you have Intelligent Octopus then Car 0 will be managed by the Octopus Energy integration, if its enabled

    +
  • +
  • +

    Each car will have it's own Home Assistant slot sensor created e.g. binary_sensor.predbat_car_charging_slot_1, +SOC planning sensor e.g predbat.car_soc_1 and predbat.car_soc_best_1 for car 1

    +
  • +
+

Balance Inverters

+

When you have two or more inverters it's possible they get out of sync so they are at different charge levels or they start to cross-charge (one discharges into another). +When enabled, balance inverters tries to recover this situation by disabling either charging or discharging from one of the batteries until they re-align.

+

Most of the Predbat configuration for balancing inverters is through a number of Home Assistant controls for Balancing Inverters, +but there is one configuration item in apps.yaml:

+
    +
  • balance_inverters_seconds - defines how often to run the inverter balancing, 30 seconds is recommended if your machine is fast enough, but the default is 60 seconds.
  • +
+

Workarounds

+

There are a number of different configuration items in apps.yaml that can be used to tweak the way Predbat operates and workaround +weirdness you may have from your inverter and battery setup.

+
    +
  • clock_skew - Skews the local (computer) time that Predbat uses (from AppDaemon).
    +Set to 1 means add a minute to the AppDaemon time, set to -1 means take a minute off the AppDaemon time. +This will change when real-time actions happen e.g. triggering a charge or discharge.
  • +
+

If your inverter's time is different to the time on the computer running Home Assistant, you may need to skew the time settings made on the inverter when you trigger charging or discharging. +Again 1 means the inverter is 1 minute fast and -1 means the inverter is 1 minute slow.

+

Separate start and end options are applied to the start and end time windows, mostly as you want to start battery activity late (not early) and finish early (not late).

+

You can adjust the charge and discharge times written to the inverter by setting the following in apps.yaml:

+
    +
  • +

    inverter_clock_skew_start, inverter_clock_skew_end - Skews the setting of the charge slot registers vs the predicted start time

    +
  • +
  • +

    inverter_clock_skew_discharge_start, inverter_clock_skew_discharge_end - Skews the setting of the discharge slot registers vs the predicted start time

    +
  • +
  • +

    battery_scaling - Default value 1.0. This setting is used to scale the battery reported SOC kWh to make it appear bigger or larger than it is +e.g. if you have an 80% depth of discharge battery that falsely reports its capacity, set this to 0.8 to report the real figure.
    +If you are going chart your battery SoC in Home Assistant then you may want to use predbat.soc_kw_h0 as your current SoC +rather than the usual givtcp__soc GivTCP entity so everything lines up

    +
  • +
  • +

    import_export_scaling - Default value 1.0. Used to scale the import & export kWh data from GivTCP if the inverter information is incorrect.

    +
  • +
  • +

    inverter_battery_rate_min - One per inverter (optional), set in Watts, when set models a "bug" in the inverter firmware +in some models where if charge or discharge rates are set to 0 you actually get a small amount of charge or discharge. +Recommended setting is 200 for Gen 1 hybrids with this issue.

    +
  • +
  • +

    inverter_reserve_max - Global, sets the maximum reserve % that maybe set to the inverter, the default is 98 as some Gen 2 inverters and +AIO firmware versions refuse to be set to 100. Comment the line out or set to 100 if your inverter allows setting to 100%.

    +
  • +
  • +

    battery_charge_power_curve - Some batteries tail off their charge rate at high soc% and this optional configuration item enables you to model this in Predbat. +Enter the charging curve as a series of steps of % of max charge rate for each soc percentage. +The default is 1.0 (full power) charge all the way to 100%. +Example from a GivEnergy 9.5kWh battery with latest firmware and Gen 1 inverter:

    +
  • +
+
  battery_charge_power_curve:
+    91 : 0.91
+    92 : 0.81
+    93 : 0.71
+    94 : 0.62
+    95 : 0.52
+    96 : 0.43
+    97 : 0.33
+    98 : 0.24
+    99 : 0.24
+    100 : 0.24
+
+

Triggers

+

The trigger feature is useful to help trigger your own automations based on Predbat determining that you have spare solar energy or battery that you would otherwise export. +For example you may turn an immersion heater or the washing machine on to consume the excess solar power.

+

The triggers count export energy until the next active charge slot only.

+

For each trigger give a name, the minutes of export needed and the energy required in that time.

+

Multiple triggers can be set at once so in total you could use too much energy if all run.

+

Each trigger specified in apps.yaml will create a Home Assistant entity called 'binary_sensor.predbat_export_trigger_name' which will be turned on when the condition is valid. +Connect this binary sensor to your automation to start whatever you want to trigger.

+

Set the name for each trigger, the number of minutes of solar export you need, and the amount of energy in kWh you will need available during that time period in apps.yaml:

+

For example:

+
export_triggers:
+  - name: "large"
+    minutes: 60
+    energy: 1.0
+  - name: "small"
+    minutes: 15
+    energy: 0.25
+
+

If you wish to trigger based on charging or discharging the battery rather than spare solar energy you can instead use the following binary sensors in Home Assistant:

+
    +
  • +

    binary_sensor.predbat_charging - Will be True when the home battery is inside a charge slot (either being charged or being held at a level). +Note that this does include charge freeze slots where the discharge rate is set to zero without charging the battery.

    +
  • +
  • +

    binary_sensor.predbat_discharging - Will be True when the home battery is inside a force discharge slot. This does not include +discharge freeze slots where the charge rate is set to zero to export excess solar only.

    +
  • +
+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/car-charge-planning/index.html b/car-charge-planning/index.html new file mode 100644 index 000000000..2b43f727a --- /dev/null +++ b/car-charge-planning/index.html @@ -0,0 +1,191 @@ + + + + + + + + Car charging planning - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + + +
  • +
  • +
+
+
+
+
+ +

Car charging planning

+

There are two ways to plan car charging slots:

+
    +
  • +

    If you have Intelligent Octopus import tariff and the Octopus Energy integration - in which case Predbat will use the slots allocated by Octopus Energy in battery prediction

    +
      +
    • Ensure octopus_intelligent_slot in apps.yaml points to the Intelligent Slot sensor in the Octopus Energy integration
    • +
    • Set switch.predbat_octopus_intelligent_charging to True
    • +
    • Information about the car's battery size will also be extracted from the Octopus Energy integration
    • +
    • You will need to set the cars current soc sensor, car_charging_soc in apps.yaml correctly to have accurate results
    • +
    • If you set car_charging_limit in apps.yaml then Predbat can also know if the car's limit is set lower than in Intelligent Octopus
    • +
    • Let the Octopus app control when your car charges
    • +
    +
  • +
  • +

    Predbat-led charging - Here Predbat plans the charging based on the upcoming low rate slots

    +
      +
    • Ensure car_charging_limit, car_charging_soc and car_charging_planned are set correctly in apps.yaml
    • +
    • Set select.predbat_car_charging_plan_time in Home Assistant to the time you want the car ready by
    • +
    • Enable switch.predbat_car_charging_plan_smart if you want to use the cheapest slots only. +If you leave this disabled then all low rate slots will be used. This may mean you need to use expert mode and change your low rate +threshold to configure which slots should be considered if you have a tariff with more than 2 import rates (e.g. flux)
    • +
    • Use an automation based on binary_sensor.predbat_car_charging_slot to control when your car charges
    • +
    +
  • +
+

NOTE: Multiple cars can be planned with Predbat.

+

See Car charging filtering and Planned car charging +in the apps.yaml settings section of the documentation.

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/configuration-guide/index.html b/configuration-guide/index.html new file mode 100644 index 000000000..aff17121b --- /dev/null +++ b/configuration-guide/index.html @@ -0,0 +1,473 @@ + + + + + + + + Configuration guide - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + + +
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  • +
+
+
+
+
+ +

Configuration guide

+

First get the basics set up, ensure you have the inverter controls configured, +you have configured apps.yaml to your setup, and the solar forecast is in place. +Make sure your energy rates are configured correctly for import and export.

+

If you have an EV try to set up the car charging sensor correctly so Predbat can tell what part of your historical load is EV charging. +You might want to also set to the car charging plan so you can predict when your car is plugged in and how much it will charge.

+

It is recommended that you create a dashboard page with all the required entities to control Predbat.

+

You should try to tune input_number.inverter_loss, input_number.battery_loss and input_number.battery_loss_discharge to the correct % loss for your system +in order to get more accurate predictions. Around 4% for each is good for a hybrid inverter. +Also set switch.inverter_hybrid to True or False depending upon if you have a Hybrid or AC-Coupled battery.

+

The setting input_number.metric_battery_cycle (expert mode) can be used to put a 'virtual cost' in pence on using your battery for charging and discharging.
+In theory if you think your battery will last say 6000 complete cycles and cost you £4000 and is 9.5kWh then each cycle is 19kWh and so the cost per cycle is £4000 / 19 / 6000 = 3.5p. +If you configure this number higher then more expensive plans will be selected which avoids charging and discharging your battery as much. +The default is 1p but can be set to 0 if you want to turn this feature off. +Note that the cycle cost will not be included in the cost predictions that Predbat produces, its just taken into account in the planning stage.
+NB: Setting this to a non-zero value will increase your daily cost, but will reduce your home battery usage.

+
    +
  • +

    input_number.forecast_plan_hours - the number of hours after the next charge slot to include in the plan, default 24 hours is the suggested amount (to match energy rate cycles)

    +
  • +
  • +

    switch.set_discharge_during_charge - If turned off disables inverter discharge during charge slots, useful for multi-inverter setups +to avoid cross charging when batteries are out of balance.

    +
  • +
+

Below is a guide to some of the electricity tariff options and a set of recommended Predbat settings for each tariff type. +In theory most tariffs will work out of the box but still it's worth reviewing your settings.

+

Fixed daily rates

+

With a fixed daily rate tariff you will just be predicting the battery levels, no charging or discharging is required although it won't hurt if you leave these options enabled.

+

You should set select.predbat_mode to 'Monitor'.

+

Cheap night rate with bad export rate (e.g. Octopus Go, Economy 7 etc)

+

In this scenario you will want to charge overnight based on the next day's solar forecast and don't want Predbat to force discharge your battery.

+

Recommended settings - these must be changed in Home Assistant once Predbat is running:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
select.predbat_modeControl ChargeYou want Predbat to calculate and control charging
input_number.predbat_best_soc_keep2.0Tweak this to control what battery level you want to keep as a backup in case you use more energy
switch.predbat_combine_charge_slotsTrueUse one big charge slot
+

If you are using expert mode then these options maybe worth reviewing:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
input_number.predbat_forecast_plan_hours24If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow
switch.predbat_combine_charge_slotsTrueAs you have just one overnight rate then one slot is fine
input_number.metric_min_improvement0Charge less if it's cost neutral
+

You should set select.predbat_mode to 'Control Charge'

+

Cheap night rate, with a good export rate (e.g. Intelligent Octopus with Octopus Outgoing)

+

Follow the instructions from the Cheap Night rate above, but also you will also want to have automatic discharge occurring when the export rates are profitable.

+ + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
select.predbat_modeControl Charge & DischargeYou want Predbat to calculate and control charging and discharging
input_number.predbat_best_soc_keep2.0Tweak this to control what battery level you want to keep as a backup in case you use more energy
switch.predbat_combine_charge_slotsTrueUse one big charge slot
+

If you are using expert mode then these options maybe worth reviewing, otherwise ignore this:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
input_number.predbat_forecast_plan_hours24If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow
switch.predbat_combine_charge_slots?Setting to False will allow charging at more expensive day rates when it's worth it to export more
input_number.metric_min_improvement0Charge less if it's cost neutral
input_number.metric_min_improvement_discharge0.1Discharge only if there is a profit
input_number.metric_battery_cycle?Higher numbers mean less charging and discharging but higher costs
input_number.predbat_best_soc_min?Can be set non-zero if you want to force a minimum charge level
+

You should set select.predbat_mode to 'Control Charge & Discharge'

+

Multiple rates for import and export (e.g. Octopus Flux & Cozy)

+

Follow the instructions from Cheap Night rate above, but also you will want to have automatic discharge when the export rates are profitable.

+

Recommended settings - these must be changed in Home Assistant once Predbat is running:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
select.predbat_modeControl Charge & DischargeYou want Predbat to calculate and control charging and discharging
input_number.predbat_best_soc_keep0.5Use the full battery without going empty
switch.predbat_combine_charge_slotsTrueUse one big charge slot
+

If you are using expert mode then these options maybe worth reviewing, otherwise ignore this:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
input_number.predbat_forecast_plan_hours24If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow
switch.predbat_combine_charge_slots?Setting to False will allow charging at more expensive day rates when it's worth it to export more
input_number.metric_min_improvement0Charge less if it's cost neutral
input_number.metric_min_improvement_discharge0.1Discharge only if there is a profit
input_number.metric_battery_cycle?Higher numbers mean less charging and discharging but higher costs
input_number.predbat_best_soc_min0Don't use non-zero otherwise all slots will be force charging
+

You should set select.predbat_mode to 'Control Charge & Discharge'

+

Half hourly variable rates (e.g. Octopus Agile)

+

Recommended settings - these must be changed in Home Assistant once Predbat is running:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
select.predbat_modeControl Charge & DischargeYou want Predbat to calculate and control charging and discharging
input_number.predbat_best_soc_keep0.5Use the full battery without going empty
switch.predbat_combine_charge_slotsTrueUse one big charge slot
+

If you are using expert mode then these options maybe worth reviewing, otherwise ignore this:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ItemValueComment
input_number.predbat_forecast_plan_hours24-48If you set this to 24 then you will have quicker updates, going to 36/48 for a longer plan
input_number.metric_min_improvement0Charge less if it's cost neutral
input_number.metric_min_improvement_discharge0.1Discharge only if there is a profit
input_number.metric_battery_cycle?Higher numbers mean less charging and discharging but higher costs
input_number.predbat_best_soc_min0Don't use non-zero otherwise all slots will be force charging
switch.calculate_fast_planFalseThe fast plan feature reduces accuracy of planning
+

You should set select.predbat_mode to 'Control Charge & Discharge'

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/creating-charts/index.html b/creating-charts/index.html new file mode 100644 index 000000000..7600dc7cc --- /dev/null +++ b/creating-charts/index.html @@ -0,0 +1,178 @@ + + + + + + + + Creating the charts - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
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+
+
+ +

Creating the charts

+

To create the fancy charts:

+ +

See the video guides for a walkthrough of what the different charts show.

+

Example charts:

+

image

+

image

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This is due to the fact that the .wy-nav-side has a + * padding-bottom of 2em, which must not necessarily align with the font-size of + * 90 % on the .rst-current-version container, combined with the padding of 12px + * above and below. These amendments fix this in two steps: First, make sure the + * .rst-current-version container has a fixed height of 40px, achieved using + * line-height, and then applying a padding-bottom of 40px to this container. In + * a second step, the items within that container are re-aligned using flexbox. + * + * https://github.com/mkdocs/mkdocs/issues/2012 + */ + .wy-nav-side { + padding-bottom: 40px; +} + +/* + * The second step of above amendment: Here we make sure the items are aligned + * correctly within the .rst-current-version container. Using flexbox, we + * achieve it in such a way that it will look like the following: + * + * [No repo_name] + * Next >> // On the first page + * << Previous Next >> // On all subsequent pages + * + * [With repo_name] + * Next >> // On the first page + * << Previous Next >> // On all subsequent pages + * + * https://github.com/mkdocs/mkdocs/issues/2012 + */ +.rst-versions .rst-current-version { + padding: 0 12px; + display: flex; + font-size: initial; + justify-content: space-between; + align-items: center; + line-height: 40px; +} + +/* + * Please note that this amendment also involves removing certain inline-styles + * from the file ./mkdocs/themes/readthedocs/versions.html. + * + * https://github.com/mkdocs/mkdocs/issues/2012 + */ +.rst-current-version span { + flex: 1; + text-align: center; +} diff --git a/customisation/index.html b/customisation/index.html new file mode 100644 index 000000000..3265cc972 --- /dev/null +++ b/customisation/index.html @@ -0,0 +1,467 @@ + + + + + + + + Customisation - Predbat Documentation + + + + + + + + + + + + + +
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+ +

Customisation

+

These are the Predbat configuration items in Home Assistant that you can modify to fit your needs, you can configure these in Home Assistant directly.

+

See Displaying output data +for information on how to view and edit these entities within +Home Assistant.

+

Predbat mode

+

The mode that Predbat operates in will change the operation, this can be configured with select.predbat_mode drop down menu as follows:

+
    +
  • Monitor
  • +
  • Control SOC Only
  • +
  • Control charge
  • +
  • Control charge & discharge
  • +
+

If the switch.predbat_set_read_only is set to True then this prevents Predbat from making modifications to the inverter settings (regardless of the configuration). +Predbat will continue making and updating its prediction plan every 5 minutes, but no inverter changes will be made. +This is useful if you want to over-ride what predbat is planning to do (e.g. your own automation), or whilst you are learning how Predbat works prior to turning it on 'in anger'.

+

NOTE: Changing the Predbat mode or the read only switch will cause Predbat to reset the inverter settings to default, this will disable +both charge and discharge, reset charge and discharge rates to full power and reset the reserve to the default setting

+

Predbat Monitor mode

+

In monitor mode Predbat will not control charging or discharging, inverter balancing will take place if enabled, the plan will show +just what is expected based on the current inverter configuration alone.

+

Predbat Control SOC Only mode

+

In Control SOC Only mode Predbat will adjust the target charge percentage (SOC target) according to the Best plan, but the charge +window will not be modified. This can be useful if you just have one fixed +charge slot per day and you only want Predbat to control the percentage.

+

CAUTION: If the charge window is disabled then no charging will take place.

+

Predbat Control Charge mode

+

In Control Charge mode Predbat will set the charge times and charge percentages according to the Best plan, charging can be enabled and +disabled by Predbat.

+

Predbat Control Charge & Discharge mode

+

In Control Charge and Discharge mode Predbat will set both charge and discharge times and control charge and discharge percentages.

+

If you have set the switch.predbat_set_discharge_freeze_only to True then forced export won't occur but Predbat can force the export +of solar power to the grid when desired.

+

Expert mode

+

Predbat has a toggle switch called switch.predbat_expert_mode which is off by default for new installs (on +by default for upgraded installs). A lot of configuration items will not be available unless expert mode is enabled. +It's recommended for new users to start without expert mode and then maybe enable it later once you become more +confident with the tool.

+ +

By default Predbat controls the inverter and updates the plan every 5 minutes, this can however use a lot of CPU power +especially on more complex tariffs like Agile when run on lower power machines such as Raspberry PIs and some thin clients.

+

You can tweak input_number.predbat_calculate_plan_every (expert mode) to reduce the frequency of replanning while +keeping the inverter control in the 5 minute slots. E.g. a value of 10 or 15 minutes should also give good results.

+

If you have performance problems leave switch.predbat_calculate_second_pass (expert mode) turned Off as it's +quite CPU intensive and provides very little improvement for most systems.

+

If you have performance problems turn switch.predbat_calculate_fast_plan (expert mode) On to help +reduce your CPU load.

+

Battery loss options

+

input_number.battery_loss accounts for energy lost charging the battery, default 0.05 is 5%

+

input_number.battery_loss_discharge accounts for energy lost discharging the battery, default 0.05 is 5%

+

input_number.inverter_loss accounts for energy loss during going from DC to AC or AC to DC, default is 0% for +legacy reasons but please adjust.

+

switch.inverter_hybrid When True you have a hybrid inverter so no inverter losses for DC charging. When false +you have inverter losses as it's AC coupled battery.

+

input_number.metric_battery_cycle (expert mode) Sets the cost in pence per kWh of using your battery for charging and discharging. +Higher numbers will reduce battery cycles at the expense of using higher energy costs. +Figures of around 1p-5p are recommended, the default is 1p per kWh.

+

input_number.predbat_metric_battery_value_scaling (expert mode) Can be used to scale the value of the energy +in the battery at the end of the plan. The battery value is accounted for in the optimisations at the lowest future +import rate including charging and inverter losses. A value of 1.0 means no change to this, while lower than 1.0 +means to value future battery levels less, greater than 1.0 will value it more (and hence hold more charge at the end of the plan).

+

Scaling and weight options

+

input_number.battery_rate_max_scaling adjusts your maximum charge/discharge rate from that reported by GivTCP +e.g. a value of 1.1 would simulate a 10% faster charge/discharge than reported by the inverter

+

switch.predbat_battery_capacity_nominal - When enabled Predbat uses the reported battery size from the Nominal field rather than from the normal GivTCP +reported size. If your battery size is reported wrongly maybe try turning this on and see if it helps.

+

input_number.load_scaling is a Scaling factor applied to historical load, tune up if you want to be more pessimistic on future consumption +Use 1.0 to use exactly previous load data (1.1 would add 10% to load)

+

input_number.load_scaling10 is a Scaling factor applied to historical load only for the PV10% scenario (this is in addition to load_scaling). +This can be used to make the 10% scenario take into account extra load usage and hence be more pessimistic while leaving the central +scenario unchanged. The default is 1.1 meaning an extra 10% load is added. This will only have an impact if the PV 10% weighting is non-zero.

+

input_number.pv_scaling is a scaling factor applied to PV data, tune down if you want to be more pessimistic on PV production vs Solcast +Use 1.0 to use exactly the Solcast data (0.9 would remove 10% from forecast)

+

input_number.pv_metric10_weight is the weighting given to the 10% PV scenario. Use 0.0 to disable this. +A value of 0.1 assumes that 1:10 times we get the 10% scenario and hence to count this in the metric benefit/cost. +A value of 0.15 is recommended.

+

Historical load data

+

The historical load data is taken from the load sensor as configured in apps.yaml and the days are selected +using days_previous and weighted using *days_previous_weight in the same configuration file

+

switch.predbat_load_filter_modal (expert mode) when enabled will automatically discard the lowest daily consumption +day from the list of days to use (provided you have more than 1 day selected in days_previous). This can be used to ignore +a single low usage day in your average calculation. By default is feature is enabled but can be disabled only in expert mode.

+

Car Charging

+

Car charging hold options

+

Car charging hold is a feature where you try to filter out previous car charging from your historical data so that +future predictions are more accurate.

+

When car_charging_hold is enabled loads of above the power threshold car_charging_threshold then you are +assumed to be charging the car and car_charging_rate will be subtracted from the historical load data.

+

For more accurate results can you use an incrementing energy sensor set with car_charging_energy in the apps.yml +then historical data will be subtracted from the load data instead.

+

car_charging_energy_scale Is used to scale the car_charging_energy sensor, the default units are kWh so +if you had a sensor in watts you might use 0.001 instead.

+
    +
  • input_number.car_charging_rate - Set to the car's charging rate in kW per hour (normally 7.5 for 7.5kWh), +but will be pulled automatically from Octopus Energy integration if enabled for Octopus Intelligent.
  • +
+

car_charging_loss gives the amount of energy lost when charging the car (load in the home vs energy added to the battery). A good setting is 0.08 which is 8%.

+

Car charging plan options

+

Car charging planning - is only used if Intelligent Octopus isn't enabled and car_charging_planned is connected correctly.

+

This feature allows Predbat to create a plan for when you car will charge, but you will have to create an automation +to trigger your car to charge using binary_sensor.predbat_car_charging_slot if you want it to match the plan.

+
    +
  • +

    car_charging_plan_time - When using Predbat-led planning set this to the time you want the car to be charged by

    +
  • +
  • +

    car_charging_plan_smart - When enabled (True) allows Predbat to allocate car charging slots to the cheapest times, +when disabled (False) all low rate slots will be used in time order.

    +
  • +
+

switch.predbat_octopus_intelligent_charging when true enables the Intelligent Octopus charging feature +which will make Predbat create a car charging plan which is taken from the Intelligent Octopus plan +you must have set octopus_intelligent_slot sensor in apps.yaml to enable this feature.

+

If Octopus Intelligent Charging is enabled the switch switch.predbat_octopus_intelligent_ignore_unplugged (expert mode) +can be used to prevent Predbat from assuming the car will be charging when the car is unplugged. This will only work correctly +if car_charging_planned is set correctly in apps.yaml to detect your car being plugged in.

+

Control how your battery behaves during car charging:

+
    +
  • car_charging_from_battery - When True the car can drain the home battery, Predbat will manage the correct level of battery accordingly. +When False home battery discharge will be prevented when your car charges, all load from the car and home will be from the grid. This is achieved +by setting the discharge rate to 0 during car charging and to the maximum otherwise, hence if you turn this switch Off you won't be able to change +your discharge rate outside Predbat. The home battery can still charge from the grid/solar in either case. Only use this if Predbat knows your car +charging plan, e.g. you are using Intelligent Octopus or you use the car slots in Predbat to control your car charging.
  • +
+

If your car does not have an SOC sensor and you are not using Octopus Intelligent you can set switch.predbat_car_charging_manual_soc +to have Predbat create input_number.predbat_car_charging_manual_soc_kwh which will hold the cars current state of charge (soc) +in kWh. You will need to manually set this to the cars current charge level before charging, Predbat will increment it during +charging sessions but will not reset it automatically.

+

Calculation options

+

See the Predbat mode setting as above for basic calculation options

+

switch.predbat_calculate_regions (expert mode) When True the a second pass of the initial thresholds is +calculated in 4 hour regions before forming the detailed plan. Is True by default but can be turned off in expert +mode.

+

switch.predbat_calculate_fast_plan (expert mode) When True the plan is calculated with a limited number of +windows to make calculations faster. When False (default) all windows are considered but planning will take a little +longer but be more accurate. +The end result is unlikely to change in fast mode as the next 8 windows are always considered in the plan, but the +longer term plan will be less accurate.

+

switch.predbat_calculate_discharge_oncharge (expert mode) When True calculated discharge slots will +disable or move charge slots, allowing them to intermix. When False discharge slots will never be placed into charge slots.

+

switch.predbat_calculate_tweak_plan (expert mode) When True causes Predbat to perform a second pass optimisation +across the next 8 charge and discharge windows in time order.

+

This can help to slightly improve the plan for tariffs like Agile but can make it worse in some fixed rate tariffs which +you want to discharge late.

+

switch.predbat_calculate_second_pass (expert mode) When True causes Predbat to perform a second pass optimisation +across all the charge and discharge windows in time order.

+

NOTE: This feature is quite slow and so may need a higher performance machine

+

This can help to slightly improve the plan for tariffs like Agile but can make it worse in some fixed rate tariffs which +you want to discharge late.

+

Battery margins and metrics options

+

input_number.best_soc_keep is the minimum battery level in kWh that Predbat will to try to keep above during the whole period of the simulation time. +This is a soft constraint only so it is possible for your SoC to drop below this - use input_number.best_soc_min for hard SoC constraint that will always be maintained. +It's usually good to have best_soc_keep set to a value above 0 to allow some margin +in case you use more energy than planned between charge slots.

+

input_number.best_soc_min (expert mode) sets the minimum charge level (in kWh) for charging during each slot and the +minimum discharge level also (set to 0 if you want to skip some slots). If you set this to a non-zero value you will need +to use the low rate threshold to control which slots you charge from or you may charge all the time.

+

input_number.best_soc_max (expert mode) sets the maximum charge level (in kWh) for charging during each slot. +A value of 0 disables this feature.

+

switch.combine_charge_slots Controls if charge slots of > 30 minutes can be combined. When disabled they will be split up, +increasing run times but potentially more accurate for planning. Turn this off if you want to enable ad-hoc import +during long periods of higher rates but you wouldn't charge normally in that period (e.g. pre-charge at day rate before +a saving session). The default is enable (True)

+

switch.combine_discharge_slots (expert mode) Controls if discharge slots of > 30 minute can be combined. When disabled +they will be split up, increasing run times but potentially more accurate for planning. The default is disabled (False)

+

input_number.metric_min_improvement (expert mode) sets the minimum cost improvement that it's worth lowering the battery SOC % for. +If it's 0 then this is disabled and the battery will be charged less if it's cost neutral. +If you use pv_metric10_weight then you probably don't need to enable this as the 10% forecast does the same thing better +Do not use if you have multiple charge windows in a given period as it won't lead to good results (e.g. Agile) +You could even go to something like -0.1 to say you would charge less even if it cost up to 0.1p more (best used with metric10)

+

input_number.metric_min_improvement_discharge (expert mode) Sets the minimum pence cost improvement it's worth doing a forced discharge (and export) for. +A value of 0.1 is the default which prevents any marginal discharges. If you increase this value (e.g. you only want to discharge/forced export if definitely very profitable), +then discharges will become less common and shorter.

+

input_number.rate_low_threshold (expert mode) When 0 (default) this is automatic but can be overridden. When non zero it sets +the threshold below average rates as the minimum to consider for a charge window, 0.8 = 80% of average rate +If you set this too low you might not get enough charge slots. If it's too high you might get too many in the +24-hour period which makes optimisation harder.

+

input_number.rate_high_threshold (expert mode) When 0 (default) this is automatic but can be overridden. When non zero it sets +the threshold above average rates as to the minimum export rate to consider exporting for - 1.2 = 20% above average rate +If you set this too high you might not get any export slots. If it's too low you might get too many in the 24-hour period.

+

input_number.metric_future_rate_offset_import (expert mode) Sets an offset to apply to future import energy rates that are +not yet published, best used for variable rate tariffs such as Agile import where the rates are not published until 4pm. +If you set this to a positive value then Predbat will assume unpublished import rates are higher by the given amount.

+

input_number.metric_future_rate_offset_export (expert mode) Sets an offset to apply to future export energy rates that are +not yet published, best used for variable rate tariffs such as Agile export where the rates are not published until 4pm. +If you set this to a negative value then Predbat will assume unpublished export rates are lower by the given amount.

+

switch.predbat_calculate_inday_adjustment (expert mode) Enabled by default with damping of 0.95. When enabled will +calculate the difference between today's actual load and today's predicated load and adjust the rest of the days usage +prediction accordingly. A scale factor can be set with input_number.predbat_metric_inday_adjust_damping (expert mode) +to either scale up or down the impact of the in-day adjustment (lower numbers scale down its impact). The in-day adjustment +factor can be see in predbat.load_inday_adjustment and charted with the In Day Adjustment chart (template can be found +in the charts template in Github).

+

Inverter control options

+

switch.set_status_notify Enables mobile notification about changes to the Predbat state (e.g. Charge, Discharge etc). On by default.

+

switch.set_inverter_notify Enables mobile notification about all changes to inverter registers (e.g. setting window, turning discharge on/off). +Off by default.

+

switch.predbat_set_charge_low_power Enables low power charging mode where the max charge rate will be limited to the +lowest possible to meet the charge target. Only really effective for charge windows >30 minutes. +Off by default.

+

switch.set_reserve_enable (expert_mode) When enabled the reserve setting is used to hold the battery charge level +once it has been reached or to protect against discharging beyond the set limit. Enabled by default.

+

switch.set_charge_freeze (expert mode) When enabled will allow Predbat to hold the current battery level while drawing +from the grid/solar as an alternative to charging. Enabled by default.

+

switch.set_discharge_freeze_only (expert mode) When enabled forced discharge is prevented, but discharge freeze can be used +(if enabled) to export excess solar rather than charging the battery. This is useful with tariffs that pay you for +solar exports but don't allow forced export (brown energy).

+

If you have switch.inverter_hybrid set to False then if switch.inverter_soc_reset (expert mode) is set to True then the +target SOC % will be reset to 100% outside a charge window. This may be required for AIO inverter to ensure it charges from solar.

+

input_number.set_reserve_min Defines the reserve percentage to reset the reserve to when not in use, a value of 4 is the +minimum and recommended to make use of the full battery

+

switch.inverter_soc_reset (expert mode) When enabled the target SOC for the inverter(s) will be reset to 100% +when a charge slot is not active, this can be used to workaround some firmware issues where the SOC target is +used for solar charging as well as grid charging. When disabled the SOC % will not be changed after a charge slot. +This is disabled by default.

+

Balance Inverters

+

When you have two or more inverters it's possible they get out of sync so they are at different charge levels or they start to cross-charge (one discharges into another). +When enabled, balance inverters tries to recover this situation by disabling either charging or discharging from one of the batteries until they re-align.

+

The apps.yaml contains a setting balance_inverters_seconds which defines how often to run the balancing, 30 seconds is recommended if your +machine is fast enough, but the default is 60 seconds.

+

Enable the switch.predbat_balance_inverters_enable switch in Home Assistant to enable this feature.

+
    +
  • switch.predbat_balance_inverters_charge - Is used to toggle on/off balancing while the batteries are charging
  • +
  • switch.predbat_balance_inverters_discharge - Is used to toggle on/off balancing while the batteries are discharging
  • +
  • switch.predbat_balance_inverters_crosscharge - Is used to toggle on/off balancing when the batteries are cross charging
  • +
  • input_number.predbat_balance_inverters_threshold_charge - Sets the minimum percentage divergence of SOC during charge before balancing, default is 1%
  • +
  • input_number.predbat_balance_inverters_threshold_discharge - Sets the minimum percentage divergence of SOC during discharge before balancing, default is 1%
  • +
+

iBoost model options

+

iBoost model, when enabled with switch.iboost_enable tries to model excess solar energy being used to heat +hot water (or similar). The predicted output from the iBoost model is returned in iboost_best.

+

The following entities are only available when you turn on iboost enable:

+

iboost_solar When enabled assumes iBoost will use solar power to boost.

+

iboost_min_soc sets the minimum home battery soc % to enable iboost solar on, default 0

+

iboost_gas When enabled assumes IBoost will operate when electric rates are lower than gas rates. +Note: Gas rates have to be configured in apps.yaml with metric_octopus_gas

+

iboost_gas_scale Sets the scaling of the gas rates used before comparing with electric rates, to account for losses

+

iboost_charging Assume IBoost operates when the battery is charging (can be combined with iboost_gas or not)

+

iboost_max_energy Sets the max energy sets the number of kwh that iBoost can consume during a day before turning off - default 3kWh

+

iboost_max_power Sets the maximum power in watts to consume - default 2400

+

iboost_min_power Sets the minimum power in watts to consume - default 500

+

You will see predbat.iboost_today entity which tracks the estimated amount consumed during the day, and resets at night

+

The binary_sensor.iboost_active entity will be enabled when IBoost should be active, can be used for automations to trigger boost

+

If you have an incrementing Sensor that tracks iBoost energy usage then you should set iboost_energy_today sensor in +apps.yaml to point to it and optionally set iboost_energy_scaling if the sensor isn't in kWh.

+

Holiday mode

+

When you go away you are likely to use less electricity and so the previous load data will be quite pessimistic.

+

Using the Home Assistant entity input_number.predbat_holiday_days_left you can set the number of full days that +you will be away for (including today). The number will count down by 1 day at midnight until it gets back to zero. +Whilst holiday days left is non-zero, Predbat's 'holiday mode' is active.

+

When Predbat's 'holiday mode' is active the historical load data will be taken from yesterday's data (1 day ago) rather than from the days_previous setting in apps.yaml. +This means Predbat will adjust more quickly to the new usage pattern.

+

If you have been away for a longer period of time (more than your normal days_previous setting) then obviously it's going +to take longer for the historical data to catch up, you could then enable holiday mode for another 7 days after your return.

+

In summary:

+
    +
  • For short holidays set holiday_days_left to the number of full days you are away, including today but excluding the return day
  • +
  • For longer holidays set holiday_days_left to the number of days you are away plus another 7 days until the data catches back up
  • +
+

Debug

+

debug_enable when on prints lots of debug, leave off by default

+

plan_debug (expert mode) when enabled adds some extra debug to the Predbat HTML plan

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/developing/index.html b/developing/index.html new file mode 100644 index 000000000..71f83f9f1 --- /dev/null +++ b/developing/index.html @@ -0,0 +1,454 @@ + + + + + + + + Developing on Predbat - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + + +
  • +
  • +
+
+
+
+
+ +

Developing on Predbat

+

Creating a fork

+

Using GitHub, take a fork of Predbat - effectively, this creates +a copy of the main repository, but in your personal space. +There, you can create branches to develop on.

+

Pull requests

+

Once you've completed your work on your branch, you can create a +pull request (PR) to merge your work back in to the main branch +of Predbat.

+

This PR should describe the work you've done in a way that +makes it easy for someone to review your work, and either +add comments or approve it.

+

Editing the code

+

There are at least a couple of ways of working on the code, outlined here.

+

Using GitHub Codespaces

+

What is GitHub Codespaces?

+

Especially if you don't need to have a running Home Assistant system +to make the changes you're interested in (e.g. for documentation, +quick fixes etc.) a really easy way to work on the code is using +GitHub Codespaces.

+

GitHub Codespaces gives you a full featured development environment. +This includes:

+
    +
  • A full IDE (a code editor), Visual Studio Code, which can be:
      +
    • Run in the browser, requiring no additional software to +be installed
    • +
    • Run in a virtual machine (VM) running in the cloud which +can connect to a copy of VS Code installed on your own +machine
    • +
    +
  • +
  • A terminal where you can run commands against your codebase +e.g. running pre-commit to run the automatic code quality checks, linting files, etc.
  • +
  • Software like mkdocs to re-generate the documentation files (and other software we may include) +pre-installed in it
  • +
+

The Codespaces environment is entirely separate from your HA +installation, so does not require any modification to your HA +setup to work with it.

+

However, you are modifying code in an environment where you +can't see HA running, so it's great for things like +updating documentation, or writing automated tests, but not +if you need to see your changes live within HA.

+

Running GitHub Codespaces

+

You may with to first install VS Code +on your machine, which does offer some benefits compared to running +Codespaces in the cloud, but this is certainly not essential, and +you'll see the same code editor and terminal, and you'll have the +same commands and Python packages available in the terminal. +The local installation is better in a small number of +scenarios e.g. if you need to connect from your browser to a specific port +on the VM, such as if you're working on the documentation.

+

Importantly, even if you do a local install of VS Code and use that +to edit your code within GitHub, the terminal, the code you're editing +any commands that you run, and any processes like mkdocs that you +may browse to are all running in the Codespaces VM. Your local +VS Code is connected to the VM through SSH. It will appear as if +the code, the terminal etc. are local, but they are not. Running +a local VS Code install connected to Codespaces will not install +Python, Python packages or anything else on your local machine.

+

Now, from your fork or branch, click on the Code button, and select the Codespaces tab. +You can create multiple environments, or use a single environment and swap +between branches in it.

+

codespaces-selection

+

Once you start your Codespaces environment, it'll take a minute to +create a VM for you, and to install the software we've asked it to +install in there. It will also clone your repository and chosen +branch into it for you, and the VM will be authenticated with GitHub +so you can commit and push straight back to your fork of Predbat on GitHub.

+

You can choose between running the IDE in the browser, or having +your local installation of VS Code connect to the environment that GitHub +Codespaces has created for you.

+

The Codespaces will be already set up with Python, along with various +Python packages (as defined in requirements.txt). The environment +is configured through the config in .devcontainer/devcontainer.json.

+

Developing locally within Home Assistant

+

To be documented later.

+

Working on the documentation

+

Overview of the Predbat documentation

+

The documentation site at https://springfall2008.github.io/batpred/ +is built from Markdown files in this repo.

+

The Markdown files used to build the documentation are in the docs/ folder, +with additional config for building the documentation site in mkdocs.yml.

+

If you're making minor changes to the documentation e.g. fixing a spelling, +you can just edit the Markdown files directly, and it will be pushed to the +main documentation site as outlined in the documentation build process +section below, once your changes are merged into main and released.

+

However, if you're doing more than that, e.g. adding new sections, working +with lists etc. we recommend you follow the instructions in +working locally on the documentation +below, as this will give you a live preview of what the documentation +will look like once it's build and published. This will avoid any +unexpected results appearing in the main documentation site.

+

If you are adding a new file, please ensure you add that file to +mkdocs.yml, so it will be linked from the menu in the sidebar.

+

The documentation build process

+

The documentation for the site is built using mkdocs, which will +already be installed if you're using a GitHub Codespaces environment.

+

For a detailed explanation of mkdocs features, please read the +mkdocs documentation.

+

As briefly covered above, mkdocs.yml contains the config for defining the documentation site, +and the documentation is built by mkdocs reading the Markdown files in the docs/ folder, +and creating HTML files from those files. mkdocs can be used locally for previewing, +but is also used as part of the documentation build process that publishes +the official documentation site.

+

The publishing of the documentation is triggered by a GitHub action, +as defined in .github/workflows/main.yml.

+

In short, after configuring the build environment, mkdocs builds the +site, then pushes the HTML produced to the gh-pages branch, +overwriting whatever was there previously.

+

GitHub will then detect a new commit on the gh-pages branch, +and that will trigger another action to run (as defined by GitHub). +This action will take the HTML files on the gh-pages branch, +and will make it available at https://springfall2008.github.io/batpred/.

+

The documentation will be published as it is, with no further +review process, so please ensure you check the documentation +that will be built before merging it in.

+

Working locally on the documentation

+

If you are making changes to the documentation, you can see +a live preview version of the documentation as it will be +built and deployed.

+

This preview version is local to your environment, is +temporary, and does not impact the published version in any way.

+

It's recommended for anything other than simple changes +like fixing spellings, adding a sentence or two. Things like +new sections, lists, new pages etc. are best previewed +due to the complications of various Markdown standards, +as what works on GitHub READMEs, for example, does not +necessarily work with the published documentation site +(which follows a more strict Markdown standard).

+

There are a number of terminal commands that you can use in the Codespaces environment. Open a terminal window in Codespaces by choosing menu > Terminal > New Terminal.

+

To run the live preview, enter mkdocs serve in the terminal window - this will cause mkdocs to build a +local temporary version of the documentation site, +and to temporarily publish it on port 8000 - it will +show the link where you can access the documentation.

+

Also, it will watch the docs/ folder, and any time you change the +files, it will rebuild the site, allowing you to see changes to +the Markdown files in your browser within a few seconds.

+

The site will continue being served until you press CTRL-C to +end the mkdocs serve command.

+

Note, accessing the site published by mkdocs serve is not +possible if you are using Codespaces to run VS Code in the browser, +but it is possible if you're using it via VS Code running locally, +due to the way in which ports on your environment are shared.

+

Coding standards

+

Expected standards

+

This section will be enhanced following discussions as we go.

+

However, here's a starting point:

+
    +
  • Variable names should be lower_case_with_underscores - this fits +with most existing variables, is a common standard for Python code, +and also allows the spell checking to check individual words within +the variable name.
  • +
+

Enforced standards

+

Certain coding standards are enforced within the repository. +Some of them can be auto-fixed, if you do a commit that +fails one of those standards; other issues will need fixing +first, as your pull request won't merge in GitHub until it passes.

+

These standards are enforced by pre-commit, +a tool which is able to run other tools to check, and potentially fix +(for certain types of issues) any mistakes you've made.

+

The .pre-commit-config.yaml file lists all checks that are +currently carried out within the repository. Bear in mind that +these checks are done according to the config within that file +in the branch that you are working in, +so if someone adds a new check, or changes some of the related settings, +it won't apply on your branch until you've merged in their changes.

+

Some of the tools have their own related config files:

+
    +
  • CSpell - .cspell.json and .cspell/custom-dictionary-workspace.txt
  • +
  • Black - pyproject.toml
  • +
  • Markdown Lint - .markdownlint.jsonc
  • +
+

Additional notes on some of the standards:

+
    +
  • CSpell - if you have the spelling check failing due to a word which is valid +but is not in the in-built dictionary, please add that word to the end +of .cspell/custom-dictionary-workspace.txt and stage those changes. +The spell-check should then pass. Note, the dictionary file will get +re-sorted alphabetically when you run pre-commit, so you'll need to +re-stage the file after it's been sorted.
  • +
+

Running the checks locally

+

If you are using a Codespaces environment, you'll already have pre-commit +installed automatically. You can run it manually, or automatically.

+

Running pre-commit manually:

+
    +
  • +

    In a terminal window, running pre-commit will run all the checks against any files that you +have modified and staged.

    +
  • +
  • +

    Alternatively, running pre-commit run --all-files will run all the checks +against all files within the repository.

    +
  • +
  • +

    Note that if pre-commit makes any changes to any files when it runs, +those changes will not be staged. You will need to stage those changes too +before committing.

    +
  • +
  • +

    You may notice pre-commit mentioning about stashing changes - this is +because when it runs, any changes that aren't staged are stashed (saved +away temporarily) so it runs against only the staged changes; +after it has run, it pulls back those stashed changes, so they appear +again (still unstaged).

    +
  • +
+

Running pre-commit automatically:

+
    +
  • +

    If you run pre-commit install in a terminal window it will install a pre-commit hook - +this is a file which tells git to run some code each type you do a +particular action (a pre-commit hook runs at the start of processing +a commit, but there are other hooks e.g. pre-push).

    +
  • +
  • +

    Now, any time you perform a commit, pre-commit will run +automatically on the staged files - this is a handy way of making sure +that you don't accidentally commit code which will fail checks later.

    +
  • +
  • +

    You can still run it manually as outlined above, in addition to the +automated checks that it will do on commits.

    +
  • +
+

Running the checks from within GitHub

+

When commits are done on pull requests, and in any other scenarios +added to the on section of.github/workflows/linting.yml, +the GitHub Actions in that file will run.

+

In particular, the pre-commit.ci lite +action will run. This uses the code here +to run the same checks that get run locally +(as described in the .pre-commit-config.yaml file).

+

This will cause your commit, branch or pull request to get either a green tick +or a red cross against it, to show whether the code passed the checks or not. +This will happen automatically, when you push code on a branch that has a +pull request.

+

In addition, if pre-commit finds any errors that it is able to fix +(e.g. a missing blank line at the end of a file, or trailing whitespace), +it will do a commit of its own to fix those problems, and will push that +commit back to your branch on GitHub. This will then trigger another run, +which should now pass.

+

Note: This means that pre-commit will be adding commits to +your branch - this will need you to be pulling changes from GitHub +so you pick up the changes that have been added by pre-commit +otherwise you will hit a problem when you next try to push a commit +on your branch. You can pull in those changes by running git pull +, which is the equivalent of running git fetch then git merge . +This is no different to working on the same branch with another developer, +but it will be different to the workflow most of us have when working +on Predbat.

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + +
+ + + + + + + + + diff --git a/energy-rates/index.html b/energy-rates/index.html new file mode 100644 index 000000000..864ff6239 --- /dev/null +++ b/energy-rates/index.html @@ -0,0 +1,343 @@ + + + + + + + + Energy rates - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + + +
  • +
  • +
+
+
+
+
+ +

Energy rates

+

Predbat needs to know what your Import and (optionally) Export rates are so it can plan the optimal way to use your battery. +Your Import and Export rates can be simple flat rates, +more complex time of day tariffs (e.g. Economy 7, Octopus Flux), +or daily/half-hourly rates that track electricity market prices (e.g. Octopus Agile or Tracker).

+

Energy rates are all configured in the apps.yaml file that's stored in either the /addon_configs/46f69597_appdaemon-predbat/apps +or the /config/appdaemon/apps/batpred/config/ directory depending on what type of Predbat installation method you have used.

+

You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) +to edit this file - see editing configuration files within Home Assistant if you need to install an editor.

+

Octopus Energy integration

+

If your electricity supplier is Octopus Energy then the simplest way to provide Predbat with your electricity pricing information +is to use the Octopus Energy integration.

+

The Octopus Energy integration connects to your Octopus Energy account and retrieves the tariffs you are on, and the current tariff rates. +If you change tariff within Octopus the integration will automatically retrieve the updated tariff information, and as tariff prices change, again they are automatically retrieved.

+

The integration also provides support for Intelligent Octopus charging to support car charging.

+

Follow the instructions provided in the Octopus Energy integration documentation to install and setup the integration.

+

Once installed, you will need to configure the integration (go to Settings / Devices & Services / Integrations / Octopus Energy then click 'Configure') +and provide the integration with your 'Octopus API key' (that you obtain from your Octopus account : Personal Details / API access).

+

CAUTION To get detailed energy rates needed by Predbat you need to go into Home Assistant and manually enable the following +Octopus Energy events which are disabled by default when the integration is installed:

+
    event.octopus_energy_electricity_xxxxxxxx_previous_day_rates
+    event.octopus_energy_electricity_xxxxxxxx_current_day_rates
+    event.octopus_energy_electricity_xxxxxxxx_next_day_rates
+
+    event.octopus_energy_electricity_xxxxxxxx_export_previous_day_rates
+    event.octopus_energy_electricity_xxxxxxxx_export_current_day_rates
+    event.octopus_energy_electricity_xxxxxxxx_export_next_day_rates
+
+    event.octopus_energy_gas_xxxxxxxx_previous_day_rates
+    event.octopus_energy_gas_xxxxxxxx_current_day_rates
+    event.octopus_energy_gas_xxxxxxxx_next_day_rates
+
+

To enable the above events:

+
    +
  • Go to Settings / Devices & Services / Integrations, choose Octopus Energy, then xx entities
  • +
  • You will see a list of entities (and events) supplied by the Octopus integration
  • +
  • Click the 'Filter' symbol on the top right hand corner (a series of lines in a downwards pointing arrow) and make sure all the options are selected
  • +
  • Then in the left hand-side search entities box, type "current_day"
  • +
  • Click on the first event that comes up, check the name is the right one
  • +
  • Click the cog wheel, then you should see the option to enable the event
  • +
  • Click the option to enable the event and press 'Update' to make the change
  • +
+

Repeat this for the other events.

+

The gas rates are only required if you have a gas boiler, an iBoost, and are using Predbat to determine whether it's cheaper to heat your hot water with the iBoost or via gas.

+

Verify that the integration is working correctly in Home Assistant by going to Developer Tools / States, and enter 'octopus' in the 'Filter entities' box. +Confirm that the Octopus entities are being populated correctly.

+

Configuring Predbat to use the Octopus Energy integration

+

The following configuration items in apps.yaml are used to configure Predbat to use the Octopus Energy integration. +They are set to a regular expression and should be auto-discovered so that Predbat automatically uses the Octopus Energy integration, +but you can comment out the regular expression lines to disable, or you set them manually.

+
    +
  • metric_octopus_import - Import rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_electricity__current_rate
  • +
  • metric_octopus_export - Export rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_electricity__export_current_rate
  • +
  • metric_octopus_gas - Gas rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_gas__current_rate
  • +
  • octopus_intelligent_slot - If you have the Octopus Intelligent GO tariff this should point to the 'slot' sensor binary_sensor.octopus_energy__intelligent_dispatching
  • +
+

metric_octopus_gas is (as above) only required to be configured if you are using Predbat to determine whether to heat your hot water via your iBoost or gas.

+

If you do not have an export rate, or are not on the Octopus Go tariff, then the appropriate lines can be commented out in apps.yaml.

+

Standing charge

+

Predbat can also (optionally) include the daily standing charge in cost predictions. +The following configuration item in apps.yaml defaults to obtaining the standing charge from the Octopus Energy integration:

+
    +
  • metric_standing_charge - Standing charge in pounds. By default points to the Octopus Energy integration sensor sensor.octopus_energy_electricity__current_standing_charge
  • +
+

You can manually change this to a standing charge in pounds, e.g. 0.50 is 50p, or delete this line from apps.yaml, or set it to zero +if you don't want the standing charge (and only have consumption usage) to be included in Predbat charts and output data.

+

Octopus Saving sessions

+

Predbat is able to automatically join you to Octopus saving sessions and plan battery activity for the saving session period to maximise your income.

+

For Predbat to automatically manage Octopus saving sessions the following additional configuration item in apps.yaml is used. +Like the electricity rates this is set in the apps.yaml template to a regular expression that should auto-discover the Octopus Energy integration.

+
    +
  • octopus_saving_session - Indicates if a saving session is active, should point to the sensor binary_sensor.octopus_energy__octoplus_saving_sessions.
  • +
+

When a saving session is available it will be automatically joined by Predbat and should then appear as a joined session within the next 30 minutes.

+

In the Predbat plan, for joined saving sessions the energy rates for import and export will be overridden by adding the assumed saving rate to your normal rate. +The assumed rate will be taken from the Octopus Energy integration and converted into pence +using the octopus_saving_session_octopoints_per_penny configuration item in apps.yaml (default is 8).

+

As the saving session import and export rates are very high compared to normal Predbat will plan additional export during the saving session period. +If necessary, a pre-charge may happen at some point during the day to maintain the battery right level for the session.

+

Note that Predbat's operational mode select.predbat_mode must be set to either 'Control charge' +or 'Control charge & discharge' for Predbat to be able to manage the battery for the saving session.

+

If you do not have an export tariff then forced export will not apply and Predbat will just ensure you have enough battery charge to see you through the saving session period.

+

If you do not want Predbat to automatically join Octopus saving sessions and manage your battery activity for the session, +simply delete or comment out the octopus_saving_session entry in apps.yaml.

+

Octopus Rates URL

+

If you do not wish to use the Octopus Energy integration and are an Octopus Energy customer then you can configure Predbat to get the electricity rates +directly online from the Octopus website.

+

In apps.yaml configure the following lines:

+
    +
  • rates_import_octopus_url to point to the appropriate import tariff URL on the Octopus website
  • +
  • rates_export_octopus_url to point to the export tariff URL
  • +
+

e.g.

+
  rates_import_octopus_url : "https://api.octopus.energy/v1/products/FLUX-IMPORT-23-02-14/electricity-tariffs/E-1R-FLUX-IMPORT-23-02-14-A/standard-unit-rates"
+  rates_import_octopus_url : "https://api.octopus.energy/v1/products/AGILE-FLEX-BB-23-02-08/electricity-tariffs/E-1R-AGILE-FLEX-BB-23-02-08-A/standard-unit-rates"
+
+  rates_export_octopus_url: "https://api.octopus.energy/v1/products/FLUX-EXPORT-BB-23-02-14/electricity-tariffs/E-1R-FLUX-EXPORT-BB-23-02-14-A/standard-unit-rates"
+  rates_export_octopus_url: "https://api.octopus.energy/v1/products/AGILE-OUTGOING-BB-23-02-28/electricity-tariffs/E-1R-AGILE-OUTGOING-BB-23-02-28-A/standard-unit-rates/"
+  rates_export_octopus_url: "https://api.octopus.energy/v1/products/OUTGOING-FIX-12M-BB-23-02-09/electricity-tariffs/E-1R-OUTGOING-FIX-12M-BB-23-02-09-A/standard-unit-rates/"
+
+

If you configure the rates_import_octopus_url then Predbat will use this instead of metric_octopus or rates_import. +Similarly rates_export_octopus_url takes precedence over metric_octopus_export or rates_export.

+

Configuring the Octopus rates URL is an expert feature and for most users the Octopus Energy integration is a simpler solution to use.

+

Rate Bands to manually configure Energy Rates

+

If you are not an Octopus Energy customer, or you are but your energy rates repeat in a simple manner, you can configure your rate bands in apps.yaml using rates_import/rates_export.

+

Add the following entries to apps.yaml to define the pattern of rates over a 24-hour period:

+
rates_import:
+  - start: "HH:MM:SS"
+    end: "HH:MM:SS"
+    rate: pence
+rates_export:
+  - start: "HH:MM:SS"
+    end: "HH:MM:SS"
+    rate: pence
+
+

start and end are in the time format of "HH:MM:SS" e.g. "12:30:00" and should be aligned to 30 minute slots normally. +rate is in pence e.g. 4.2

+

start and end can be omitted and Predbat will assume that you are on a single flat rate tariff.

+

If there are any gaps in the 24-hour period then a zero rate will be assumed.

+

Manually over-riding energy rates

+

You can also override the energy rates (regardless of whether they are set manually or via the Octopus Energy integration) by using the override feature in apps.yaml.

+

Rate override is used to set the specific date and time period where your rates are different, e.g. an Octopus Power Up session (zero rate for an hour or two), +or the British Gas half-price electricity on Sunday's.

+

Unfortunately there aren't any API's available to feed this information automatically into Predbat so you will have to edit apps.yaml manually +to set the appropriate rate over-ride dates and times:

+
rates_import_override:
+  - date : "YYYY-MM-DD"
+    start : "HH:MM:SS"
+    end : "HH:MM:SS"
+    rate : pence
+rates_export_override:
+  - date : "YYYY-MM-DD"
+    start : "HH:MM:SS"
+    end : "HH:MM:SS"
+    rate : pence
+
+

date is in the date format of "YYYY-MM-DD" e.g. "2023-09-09", start and end in "HH:MM:SS" time format e.g. "12:30:00", and rate in pence.

+

Rate offsets

+

If you are on an Agile or Tracker tariff you can tune future unknown energy rates by adjusting the entities input_number.predbat_metric_future_rate_offset_import (expert mode) +and input_number.predbat_metric_future_rate_offset_export (expert mode) inside Home Assistant to set the predicted offset for future unknown rates.

+

Future Agile energy rates

+

In the energy market it's possible to calculate the Octopus Agile rates from around 10am UK time using public data, you can +enable this in apps.yaml for Import, Export or both. This will approximate next day's rates based on the spot prices. +The approximation is only used until the real Octopus Agile rates are released around 4pm.

+
    +
  • futurerate_url - URL of future energy market prices; this should not normally need to be changed
  • +
  • futurerate_adjust_import and futurerate_adjust_export - Whether tomorrow's predicted import or export prices should be adjusted based on energy market prices or not. +Set these depending upon whether you have an agile tariff for import, export or both
  • +
  • futurerate_peak_start and futurerate_peak_end - during the peak period Octopus apply an additional peak-rate price adjustment. +These configuration items enable the peak-rate hours to be adjusted
  • +
  • futurerate_peak_premium_import and futurerate_peak_premium_export - the price premium (in pence) to be added to the energy market prices during the above-defined peak period
  • +
+

CAUTION: You may violate the terms and conditions of the Nordpool site if you use this data and as such the authors of +Predbat accept no responsibility for any violations:

+

https://www.nordpoolgroup.com/en/About-us/terms-and-conditions-for-useofwebsite/

+
futurerate_url: '<https://www.nordpoolgroup.com/api/marketdata/page/325?currency=GBP>'
+futurerate_adjust_import: True
+futurerate_adjust_export: False
+futurerate_peak_start: "16:00:00"
+futurerate_peak_end: "19:00:00"
+futurerate_peak_premium_import: 14
+futurerate_peak_premium_export: 6.5
+
+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/faq/index.html b/faq/index.html new file mode 100644 index 000000000..f689f6629 --- /dev/null +++ b/faq/index.html @@ -0,0 +1,277 @@ + + + + + + + + FAQ - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
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  • + + +
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  • +
+
+
+
+
+ +

FAQ

+

I've installed Predbat but I don't see the correct entities

+
    +
  • First look at predbat.status in Home Assistant and the AppDaemon.log (which can be found in the list of log files in the System/Log area of the GUI). +See if any errors are warnings are found. If you see an error it's likely something is configured wrongly, +check your entity settings are correct.
  • +
  • Make sure Solcast is installed and it's auto-updated at least a couple of times a day (see the Solcast instructions). +The default solcast sensor names maybe wrong, you might need to update the apps.yaml config to match your own names +(some people don't have the solcast_ bit in their names)
  • +
  • Did you configure AppDaemon apps_dir correctly in appdaemon.yaml?
  • +
+

Why is my predicted charge % higher or lower than I might expect?

+
    +
  • Predbat is based on costing, so it will try to save you money. If you have the PV 10% option enabled it will also +take into account the more worse case scenario and how often it might happen, so if the forecast is a bit unreliable +it's better to charge more and not risk getting stung importing.
  • +
  • Have you checked your energy rates for import and export are correct, maybe check the rates graph and confirm. +If you do something like have export>import then Predbat will try to export as much as possible.
  • +
  • Have you tuned Solcast to match your output accurately?
  • +
  • Have you tuned best_soc_keep settings
  • +
  • Do you have predicted car charging during the time period?
  • +
  • You can also tune load_scaling and pv_scaling to adjust predictions up and down a bit
  • +
  • Maybe your historical data includes car charging, you might want to filter this out using car_charging_hold (see below)
  • +
+

Why didn't the slot actually get configured?

+
    +
  • Are you in read-only mode?
  • +
  • Do you have the predbat_mode set to Control Charge (or Charge & Discharge)?
  • +
+

The charge limit keeps increasing/decreasing in the charge window or is unstable

+
    +
  • Check you don't have any other automations running that adjust GivTCP settings during this time. Some people had +a script that changes the reserve %, this will cause problems - please disable other automations and retry.
  • +
+

I changed a config item but it made no difference?

+
    +
  • You might have to wait a few minutes until the next update cycle. Depending on the speed of the computer that Predbat is running on, it can take 1-5 minutes for Predbat to run through.
  • +
+

It's all running but I'm not getting very good results

+
    +
  • You might want to tune best_soc_keep to set a minimum target battery level, e.g. I use 2.0 (for 2kWh, which is just over 20% on a 9.5kWh battery). +If you set best_soc_keep too high then predbat could need to charge the battery in unfavourable import rates, so try to set it to a fairly low value, +especially if you have a small battery. If you set it to zero then predbat may not charge at all, so use 0.1 as a minimum.
  • +
  • Have a read of the energy rates configuration guide as depending on your tariff different settings maybe required
  • +
  • Check your solar production is well calibrated (you can compare solcast vs actually in the Home Assistant energy tab or on the GivEnergy portal)
  • +
  • Make sure your inverter max AC rate has been set correctly
  • +
  • If you have an EV that you charge then you will want some sort of car charging sensor or use the basic car charging hold feature or your load predictions maybe unreliable
  • +
  • Do you have a solar diverter? If so maybe you want to try using the iBoost model settings.
  • +
  • Perhaps set up the calibration chart and let it run for 24 hours to see how things line up
  • +
  • If your export slots are too small compared to expected check your inverter_limit is set correctly (see below)
  • +
+

Predbat is causing warning messages in the Home Assistant Core log

+
    +
  • If you have a large input_number.predbat_forecast_plan_hours then you may see warning +messages in the Home Assistant Core log about the size of the predbat.plan_html entity. +This is just a warning, the entity isn't stored in the database, but you can suppress it by adding the following +to your configuration.yaml:
  • +
+
# Filter out 'message too large' warnings from Predbat
+logger:
+  default: warning
+  filters:
+    homeassistant.components.recorder.db_schema:
+      - "State attributes for predbat.plan_html exceed maximum size of 16384 bytes. This can cause database performance issues; Attributes will not be stored"
+
+

Error - metric_octopus_import not set correctly or no energy rates can be read

+

If you get this error in the Predbat log file:

+
    +
  • Check that the Octopus integration is working and that event.octopus_energy_electricity__current_day_rates +and sensor.octopus_electricity_energy__current_rate are both populated by the integration.
  • +
  • Ensure that you have followed the Octopus Integration Installation instructions, including enabling the Octopus Integration events.
  • +
  • If you been using an older version of the Octopus integration and have upgraded to version 9 or above, then you may find that your energy sensors are named sensor.electricity__current_rate +(i.e. no 'octopus_energy_' prefix) but the 'event' entities have the 'octopus_energy' prefix.
    +If the 'event' and 'sensor' entities are not consistently named then Predbat will not be able to find the event entities if the sensor names don't match what's expected.
    +To fix this, uninstall the Octopus integration, reboot Home Assistant, +delete all the old Octopus sensors, and re-install the Octopus Integration.
  • +
+

WARN: No solar data has been configured

+

If you get this warning message in the Predbat log file:

+
    +
  • Ensure that you have installed and configured Solcast correctly
  • +
  • Check the Solcast integration in Home Assistant is configured and enabled (go to Settings / Integrations / Solcast )
  • +
  • Verify the solar forecast has been populated in Home Assistant by going to Developer Tools / States, filtering on 'solcast', +and checking that you can see the half-hourly solar forecasts in the Solcast entities
  • +
  • If you can see the solcast entities but there are no forecast PV figures, try running the 'Solcast update' automation you created, and check again the solcast entities
  • +
  • Check sensor.solcast_pv_api_limit (it's normally 10 for new Solcast accounts) meaning you can call the Solcast API 10 times a day +(but if you have two solar arrays, e.g. East/West) then retrieving the forecast will count as two API calls. +Compare this to sensor.solcast_pv_api_used to see how many Solcast API calls you have made today +(alternatively, you can confirm how many API calls you have made today by logging into your solcast account). +If you've run out of API calls you will have to wait until midnight GMT for the API count to reset. +It's recommended that you don't include the Solcast forecast within your GivEnergy portal to avoid running out of API calls.
  • +
  • Check the Solcast server API status is OK
  • +
+

I have another problem not listed above

+

If you are still having trouble feel free to raise a Github ticket for support

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/images/codespaces-selection.png b/images/codespaces-selection.png new file mode 100644 index 000000000..484250818 Binary files /dev/null and b/images/codespaces-selection.png differ diff --git a/images/predbat-status-issue.png b/images/predbat-status-issue.png new file mode 100644 index 000000000..f599cb3cc Binary files /dev/null and b/images/predbat-status-issue.png differ diff --git a/img/favicon.ico b/img/favicon.ico new file mode 100644 index 000000000..e85006a3c Binary files /dev/null and b/img/favicon.ico differ diff --git a/index.html b/index.html new file mode 100644 index 000000000..8d9a521ec --- /dev/null +++ b/index.html @@ -0,0 +1,177 @@ + + + + + + + + Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + +
  • +
  • +
+
+
+
+
+ +

Introduction

+

Home battery prediction and automatic charging for Home Assistant with GivTCP

+

Also known by some as Batpred or Batman!

+

image

+
Copyright (c) Trefor Southwell October 2024 - All rights reserved
+This software maybe used at not cost for personal use only
+No warranty is given, either expressed or implied
+
+

For support please raise a Github ticket or use the GivTCP Facebook page:

+

https://www.facebook.com/groups/615579009972782

+

For support specific to the Solis inverter you can use the Solis Facebook Group:.

+

If you want to buy me a beer then please use Paypal - tdlj@tdlj.net +image

+

image

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + + Next » + + +
+ + + + + + + + + + + diff --git a/install/index.html b/install/index.html new file mode 100644 index 000000000..db03d5502 --- /dev/null +++ b/install/index.html @@ -0,0 +1,451 @@ + + + + + + + + Install details - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + + +
  • +
  • +
+
+
+
+
+ +

Install

+

These instructions will take you through the process of installing and configuring Predbat for first time use.

+

It's recommended that you watch the Video Guides before you start.

+

A level of familiarity with the basics of Home Assistant, Add-on's, Integrations, Entities and File Editing is assumed. +There are plenty of "Home Assistant basics" tutorials on YouTube, but if you get stuck, please read the FAQ's +and if necessary raise a Github ticket for support.

+

Inverter Control Integration install (GivTCP/SolaX-ModBus)

+

The Integration that communicates with your inverter will be depend on the brand of inverter you have:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
BrandIntegrationGithub Link
GivEnergyGivTCPhttps://github.com/britkat1980/giv_tcp
SolisSolaX ModBushttps://github.com/wills106/homeassistant-solax-modbus
SofarSofar MQTThttps://github.com/cmcgerty/Sofar2mqtt
+

Please see Other Inverters for details on how Solis, Solax and Sofar install details.

+
    +
  • Follow the installation and configuration instructions appropriate for your inverter so that Home Assistant is able to 'see' and manage your inverter.
  • +
  • You will need at least 24 hours history in Home Assistant for Predbat to work correctly, the default is 7 days (but you configure this back to 1 day if you need to).
  • +
+

Editing Configuration Files in Home Assistant

+

The basic configuration for Predbat is stored in a configuration file called apps.yaml. +A standard template apps.yaml file will be installed as part of the Predbat installation and you will need to edit and customise this configuration file for your own system setup.

+

You will therefore need a method of editing configuration files within your Home Assistant environment.

+

There are severals ways to achieve this in Home Assistant, but two of the simplest are to use either the File Editor or Studio Code Server add-on's. +Whichever you use is a personal preference. File Editor is a bit simpler, Studio Code Server is more powerful +but does require HACS (the Home Assistant Community Store) to be installed first.

+

If you do not have one of these file editors already installed in Home Assistant:

+
    +
  • For Studio Code Server you will need to install HACS first if you don't currently have it installed
  • +
  • Go to Settings / Add-ons / Add-on Store (bottom right)
  • +
  • Scroll down the add-on store list, to find either 'File editor' or 'Studio Code Server' as appropriate, click on the add-on, click 'INSTALL'
  • +
  • Once the editor has been installed, ensure that the 'Start on boot' option is turned on, and click 'START' to start the add-on
  • +
+

Thereafter whenever you need to edit a configuration file in Home Assistant you can navigate to Settings / Add-on's / / 'OPEN WEB UI'

+

If you are using the File Editor to edit Predbat's configuration files, you will need to turn off Enforce Basepath to enable you to access files in the appdaemon directory:

+
    +
  • From the File editor add-on page, click on the 'Configuration' tab to change this setting):
    +image
  • +
+

AppDaemon-Predbat combined install

+

The simplest way to install Predbat now is with a combined AppDaemon/Predbat add-on. +This is a fork of AppDaemon which automatically includes an install of Predbat.

+

Installing the combined AppDaemon-predbat add-on is thus simpler for new users as they do not need to install HACS, AppDaemon and Predbat as three separate installation steps. +If you are already running AppDaemon then the original installation method for Predbat still exists, is still supported, and is described below in Predbat Installation into AppDaemon.

+

To install the combined AppDaemon-predbat add-on:

+
    +
  • Go to Settings / Add-ons / Add-on Store (bottom right), click the three dots in the top right, then Repositories and type +https://github.com/springfall2008/appdaemon-predbat', click ADD, then CLOSE.
  • +
  • In order to refresh the list of available add-on's, navigate back through Settings / Add-ons / Add-on Store, scroll down and select 'AppDaemon with Predbat'
  • +
  • Click INSTALL and wait for the add-on to be installed
  • +
  • Once it has finished installing, ensure that the 'Start on boot' option is turned on, then click 'START'
  • +
+

NOTE: Throughout the rest of the Predbat documentation you will find reference to the Predbat configuration file apps.yaml and the Predbat logfile.

+

These are located under the Home Assistant directory /addon_configs/46f69597_appdaemon-predbat which contains:

+
    +
  • predbat.log - Predbat's active logfile that reports detail of what Predbat is doing, and details of any errors
  • +
  • apps/apps.yaml - Predbat's configuration file which will need to be customised to your system and requirements. This configuration process is described below.
  • +
+

You can use your file editor (i.e. 'File editor' or 'Studio Code Server' add-on) to open the directory /addon_configs/46f69597_appdaemon-predbat and view these files.

+

If you have used the AppDaemon-predbat add-on installation method you do not need to install HACS or AppDaemon so you can skip directly to Solcast install below.

+

Predbat installation into AppDaemon

+

This is the "classic" way of installing Predbat, to firstly install HACS (the Home Assistant Community Store), then install the AppDaemon add-on, +and finally install Predbat from HACS to run within AppDaemon.

+

HACS install

+

Predbat and AppDaemon are available through the Home Assistant Community Store (HACS). You can install Predbat manually (see below) but its usually easier to install it through HACS.

+ +

AppDaemon install

+

Predbat is written in Python and runs on a continual loop (default every 5 minutes) within the AppDaemon add-on to Home Assistant. +The next task therefore is to install and configure AppDaemon.

+
    +
  • Install the AppDaemon add-on https://github.com/hassio-addons/addon-appdaemon
  • +
  • Once AppDaemon has finished installing, ensure that the 'Start on boot' option is turned on, then click 'START'
  • +
  • You will need to edit the appdaemon.yaml configuration file for AppDaemon and so will need to have either +the File Editor or Studio Code Server add-on's installed first
  • +
  • Find the appdaemon.yaml file in the directory /addon_configs/a0d7b954_appdaemon: image
  • +
  • Add to the appdaemon.yaml configuration file:
      +
    • A section app_dir which should refer to the directory /homeassistant/appdaemon/apps where Predbat will be installed
    • +
    • Ensure that the time_zone is set correctly (e.g. Europe/London)
    • +
    • Add thread_duration_warning_threshold: 120 in the appdaemon section
    • +
    +
  • +
  • It's recommended you also add a logs section and specify a new logfile location so that you can see the complete logs, I set mine +to /homeassistant/appdaemon/appdaemon.log and increase the logfile maximum size and number of logfile generations to capture a few days worth of logs.
  • +
+

Example AppDaemon config in appdaemon.yaml:

+
appdaemon:
+  latitude: 52.379189
+  longitude: 4.899431
+  elevation: 2
+  time_zone: Europe/London
+  thread_duration_warning_threshold: 120
+  plugins:
+    HASS:
+      type: hass
+  app_dir: /homeassistant/appdaemon/apps
+http:
+  url: http://homeassistant.local:5050
+admin:
+api:
+hadashboard:
+
+# write log records to a file, retaining 9 versions, rather than the standard appdaemon log
+logs:
+  main_log:
+    filename: /homeassistant/appdaemon/appdaemon.log
+    log_generations: 9
+    log_size: 10000000
+
+

CAUTION: If you are upgrading AppDaemon from an older version to version 0.15.2 or above you need to follow these steps to ensure Predbat continues working. +These are only required if you are upgrading AppDaemon from an old version, they're not required for new installations of AppDaemon:

+
    +
  • Make sure you have access to the HA filesystem, e.g. I use the Samba add-on and connect to the drives on my Mac, but you can use ssh also.
  • +
  • Update AppDaemon to the latest version
  • +
  • Go into the directory /addon_configs/a0d7b954_appdaemon and edit appdaemon.yaml. You need to add app_dir (see above) to point to the +old location and update your logfile location (if you have set it). You should remove the line that points to secrets.yaml +(most people don't use this file) or adjust it's path to the new location (/homeassistant/secrets.yaml)
  • +
  • Move the entire 'apps' directory from /addon_configs/a0d7b954_appdaemon (new location) to /config/appdaemon (the old location)
  • +
  • Restart AppDaemon
  • +
  • Check it has started and confirm Predbat is running correctly again.
  • +
+

Install Predbat through HACS

+

hacs_badge

+

If you install Predbat through HACS, once installed you will get automatic updates for each new release of Predbat!

+
    +
  • In HACS, click on Automation
  • +
  • Click on the three dots in the top right corner, choose Custom Repositories
  • +
  • Add https://github.com/springfall2008/batpred as a custom repository of Category 'AppDaemon' and click 'Add'
  • +
  • Click Explore and download repositories (bottom right), type 'Predbat' in the search box, select the Predbat Repository, then click 'Download' to install the Predbat app.
  • +
+

NOTE: Throughout the rest of the Predbat documentation you will find reference to the Predbat configuration file apps.yaml and the Predbat logfile.

+

These are located under the Home Assistant directory /config/appdaemon/ which contains:

+
    +
  • appdaemon.log - AppDaemon and Predbat's active logfile that reports detail of what Predbat is doing, and details of any errors
  • +
  • apps/batpred/config/apps.yaml - Predbat's configuration file which will need to be customised to your system and requirements. This configuration process is described below.
  • +
+

Predbat manual install

+

A manual install is suitable for those running Docker type systems where HACS does not function correctly and you had to manually install AppDaemon.

+

Note: Not recommended if you are using HACS

+
    +
  • Copy the file apps/predbat/predbat.py to the /config/appdaemon/apps/ directory in Home Assistant (or wherever you set appdaemon app_dir to)
  • +
  • Copy apps/predbat/apps.yaml to the /config/appdaemon/apps/ directory in Home Assistant (or wherever you set appdaemon app_dir to)
  • +
  • +

    Edit in Home Assistant the /config/appdaemon/apps/apps.yaml file to configure Predbat

    +
  • +
  • +

    If you later install with HACS then you must move the apps.yaml into /config/appdaemon/apps/predbat/config

    +
  • +
+

Solcast Install

+

Predbat needs a solar forecast in order to predict solar generation and battery charging.

+

If you don't have solar then use a file editor to comment out the following lines from the Solar forecast part of the apps.yaml configuration:

+
  pv_forecast_today: re:(sensor.(solcast_|)(pv_forecast_|)forecast_today)
+  pv_forecast_tomorrow: re:(sensor.(solcast_|)(pv_forecast_|)forecast_tomorrow)
+  pv_forecast_d3: re:(sensor.(solcast_|)(pv_forecast_|)forecast_(day_3|d3))
+  pv_forecast_d4: re:(sensor.(solcast_|)(pv_forecast_|)forecast_(day_4|d4))
+
+

If you do have solar panels its recommended to use the Solcast integration to automatically retrieve your forecast solar generation. +Predbat is configured to automatically discover the Solcast forecast entities in Home Assistant.

+

Install the Solcast integration (https://github.com/oziee/ha-solcast-solar), create a Solcast account, +configure details of your solar arrays, and request an API key that you enter into the Solcast integration in Home Assistant.

+

Note that Predbat does not update Solcast for you so you will need to create your own Home Assistant automation that updates the solar forecast a few times a day +(e.g. dawn, dusk, and just before your nightly charge slot).

+

Example Solcast update automation script:

+
alias: Solcast update
+description: "Update Solcast solar forecast"
+trigger:
+  - platform: time
+    at: "23:00:00"
+  - platform: time
+    at: "12:00:00"
+  - platform: time
+    at: "04:00:00"
+condition: []
+action:
+  - service: solcast_solar.update_forecasts
+    data: {}
+mode: single
+
+

Manually run the automation and then make sure the Solcast integration is working in Home Assistant by going to Developer Tools / States, filtering on 'solcast', +and checking that you can see the half-hourly solar forecasts in the Solcast entities.

+

Energy Rates

+

Predbat needs to know what your electricity import and export rates are in order to optimise battery charging and discharging to minimise your expenditure.

+

These rates are configured in Predbat's apps.yaml configuration file. Follow the instructions in the Energy Rates document.

+

Note: that if you are using the Octopus integration the 'sensor.octopus_xxx' and 'event.octopus_xxx' entities must have a similar pattern of +names for Predbat to work correctly - see the FAQ's if they are not.

+

Configuring Predbat

+

You will need to use a file editor (either the File editor or Studio Code Server add-on) to edit the apps.yaml file in Home Assistant +to configure Predbat - see Configuring apps.yaml.

+

When Predbat starts up initially it will perform a sanity check of the AppDaemon configuration itself and confirm the right files are present. +You will see this check in the log, should it fail a warning will be issued and predbat.status will also reflect the warning. +While the above warning might not prevent Predbat from starting up, you should fix the issue ASAP as it may cause future problems.

+

Predbat Output and Configuration Controls

+

As described above, the basic configuration of Predbat is held in the apps.yaml configuration file.

+

When Predbat first runs it will create a number of output and configuration control entities in Home Assistant which are used to fine-tune how Predbat operates. +The entities are all prefixed predbat and can be seen (and changed) from the Settings / Devices & Services / Entities list in Home Assistant.

+

It is recommended that you create a dashboard page with all the required entities to control Predbat +and another page to display Predbat's charging and discharging plan for your battery.

+

The Output Data section describes these points in more detail.

+

The Home Assistant entity predbat.status contains details of what status Predbat is currently in (e.g. Idle, Charging, Error). +Detailed progress messages and error logging is written to the Predbat logfile which you can view within Home Assistant using a file editor.

+

The Predbat Configuration Guide gives an overview of the main Predbat configuration items and +detail of 'standard Predbat configuration' settings for different electricity tariff types - e.g. a cheap overnight rate, +multiple import rates during the day, and variable tariffs such as Agile, etc.

+

The detailed Predbat Customisation Guide details all the Predbat configuration items (switches, input numbers, etc) in Home Assistant, and what each of them does.

+

Ready to light the touch-paper

+

By now you should have successfully installed and configured Predbat in AppDaemon and the other components it is dependent upon (e.g. GivTCP, Solcast, Octopus Integration).

+

You have checked the Predbat AppDaemon log file doesn't have any errors (there is a lot of output in the logfile, this is normal).

+

You have configured predbat's control entities, created a couple of dashboard pages to control and monitor Predbat, and are ready to start Predbat running.

+

In order to enable Predbat you must delete the 'template: True' line in apps.yaml once you are happy with your configuration.

+

You may initially want to set select.predbat_mode to Monitor to see how Predbat operates, e.g. by studying the Predbat Plan.

+

Once you are happy with the plan Predbat is producing, and are ready to let Predbat start controlling your inverter, set select.predbat_mode +to the correct mode of operation for your system.

+

Updating Predbat

+

Note that future updates to Predbat will not overwrite the apps.yaml configuration file that you have tailored to your setup. +You may therefore need to manually copy across any new apps.yaml settings from the Template apps.yaml for new features.

+

HACS Update

+

HACS checks for updates and new releases only once a day by default, you can however force it to check again, or download a specific version +by using the 'Redownload' option from the top-right three dots menu for Predbat in the HACS Automation section.

+

NOTE: If you update Predbat through HACS you may need to restart AppDaemon as it sometimes reads the config wrongly during the update. +(If this happens you will get a template configuration error in the entity predbat.status).
+Go to Settings, Add-ons, AppDaemon, and click 'Restart'.

+

Predbat built-in update

+

Predbat can now update itself, just select the version you want from the select.predbat_update drop down menu, the latest version will be at the top of the list. +Predbat will update itself and automatically restart.

+

Alternatively, if you turn on switch.predbat_auto_update, Predbat will automatically update itself as new releases are published on Github.

+

If you have used the Combined AppDaemon and Predbat add-on installation method then +once installed and configured you should update Predbat to the latest version by using the select.predbat_update selector or by enabling the switch.predbat_auto_update.

+

Manual update of Predbat

+

You can go to Github and download predbat.py from the releases tab and then manually copy this file +over the existing version in /config/appdaemon/apps/batpred/ manually.

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/installation-summary/index.html b/installation-summary/index.html new file mode 100644 index 000000000..f1be63110 --- /dev/null +++ b/installation-summary/index.html @@ -0,0 +1,212 @@ + + + + + + + + Install summary - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + + +
  • +
  • +
+
+
+
+
+ +

Installation summary

+

Please see the sections below for how to achieve each step. This is just a checklist of things:

+
    +
  1. Before you start, its recommended that you watch the step by step installation videos, +see the video guides section for those and other videos
  2. +
  3. Make sure the right inverter control module is installed and running - GivTCP or Solax install
  4. +
  5. Install a file editor (either the File editor or Studio Code Server add-on) to enable you to edit configuration files if you haven't already - Editing configuration files
  6. +
  7. Install Predbat and AppDaemon, either: +
  8. +
  9. Install Solcast if you haven't already Solcast install. +Create an automation to update Solcast a times a day, and check that you see the Solcast data in Home Assistant
  10. +
  11. Follow the Energy Rates instructions to tell Predbat what your import and export energy rates are. +If you use Octopus Energy then this includes installing the Octopus Energy integration (if you haven't already) - Octopus Energy
  12. +
  13. Edit Predbat's apps.yaml configuration file to to match your system - apps.yaml settings
    +The apps.yaml file will be in either the directory /addon_configs/46f69597_appdaemon-predbat/apps +or /config/appdaemon/apps/predbat/config/ depending on which Predbat install method you used.
      +
    • Inverter settings match the names in GivTCP - should be automatic (but if you have 2 names you will have to edit apps.yaml)
        +
      • You have set the right number of inverters (num_inverters)
      • +
      • Adjust your inverter_limit and export_limit as required
      • +
      +
    • +
    • You have your energy rates set correctly either using Octopus Energy integration or entered manually
    • +
    • That the Solcast plugin is matching the configuration correctly - should be automatic
    • +
    • If you have a car charging sensor you might want to add that also to help make predictions more accurate
    • +
    +
  14. +
  15. Add the Predbat entities to your dashboard - Output data
  16. +
  17. Follow the Configuration Guide to set 'standard' Predbat configuration settings depending on your import and export tariffs
  18. +
  19. The detailed Customisation Guide lists all Predbat's controls and settings in Home Assistant that can be tuned for your system
  20. +
  21. Set up the Predbat Plan card so you can check what Predbat is planning to do - Create the Predbat Plan card
  22. +
  23. Set up the Apex Charts for other views on what Predbat is doing - Creating the charts
  24. +
  25. Then check Predbat is working correctly:
      +
    • Look at the Predbat AppDaemon log file and make sure you have no errors or warnings that are unexpected
    • +
    • Comment out or delete the template: True line in apps.yaml when you are ready to start Predbat
    • +
    • The predbat.status in Home Assistant should be 'Idle' (if there are any errors then they are reported here too)
    • +
    • Start with select.predbat_mode set to 'Monitor' but remember to change it later to enable Predbat to control your inverter
    • +
    +
  26. +
  27. Look at the FAQ for help
  28. +
+

Overview of the key configuration elements:

+

image

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
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+ + +
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+
+
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+
+ +

Other Inverters

+

PredBat was originally written for GivEnergy inverters using the GivTCP integration but this is now being extended to other models:

+ +

Note that support for all these inverters is in various stages of development. Please expect things to fail and report them as Issues on Github. +Please also ensure you have set up enhanced logging in AppDaemon as described here.

+

Solis Inverters

+

To run PredBat with Solis hybrid inverters, follow the following steps:

+
    +
  1. Install PredBat as per the Installation Summary
  2. +
  3. Ensure that you have the Solax Modbus integration running. There are a number of entities which this integration disables by default that you + will need to enable via the Home Assistant GUI:
  4. +
+ + + + + + + + + + + + + + + + + +
NameDescription
sensor.solisx_rtcReal Time Clock
sensor.solisx_battery_powerBattery Power
+
    +
  1. Instead of apps.yaml use ginlong_solis.yaml from this Repo as your starting template. + The majority of settings should be correct but please check. + You will need to un-comment the template line to enable it. Save it to the config/appdaemon/apps/predbat/config folder.
  2. +
  3. Ensure that the inverter is set Control Mode 35 - on the Solax integration this is Timed Charge/Discharge. + If you want to use the Reserve functionality within PredBat you will need to select Backup/Reserve (code 51) instead but be aware that + this is not fully tested. In due course these mode settings will be incorporated into the code.
  4. +
+

Solax Inverters

+

Please see this ticket in Github for ongoing discussion: https://github.com/springfall2008/batpred/issues/259

+

Sofar Inverters

+

For this integration the key elements are:

+
    +
  • Hardware - sofar2mqtt EPS board - Relatively easy to solder and flash, or can be bought pre-made.
  • +
  • Software - Sofar MQTT integration - MQTT integration
  • +
  • Home Assistant configuration - sofar_inverter.yaml package (in templates directory) +with the MQTT sensors. This is the default with a couple of additional inputs to support battery capacity. This should be installed in Home Assistant.
  • +
  • Predbat configuration - sofar.yaml template for Predbat (in templates directory). +This file should be copied to apps.yaml
  • +
+

This integration has various limitations, it can charge and discharge the battery but does not have finer control over reserve and target SOC%

+

Note: You will need to change the min reserve in Home Assistant to match your minimum battery level.

+

Please see this ticket in Github for ongoing discussions: https://github.com/springfall2008/batpred/issues/395

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/output-data/index.html b/output-data/index.html new file mode 100644 index 000000000..c779b6c03 --- /dev/null +++ b/output-data/index.html @@ -0,0 +1,448 @@ + + + + + + + + Output data - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
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  • +
+
+
+
+
+ +

Output data

+

Displaying output data

+

Each Predbat config item has an input_number or switch associated with it, you can find an auto-generated dashboard for your +configuration in your AppDaemon configuration area under the filename predbat_dashboard.yaml. +You will need to open that file in a Home Assistant file editor and copy the contents into a new dashboard page.

+

You can also create a dashboard page using dynamic-entities-card.yaml for a +dynamically created list of all Predbat entities which groups the entities by type and is collapsed by default to prevent screen clutter. Requires lovelace-collapsable-cards +(https://github.com/RossMcMillan92/lovelace-collapsable-cards) +and lovelace-auto-entities (https://github.com/thomasloven/lovelace-auto-entities) +to be installed via HACS as well as the stock vertical stack card. Credit @DJBenson for the code.

+

The Predbat Plan card is very useful for seeing the plan that Predbat has created - Create the Predbat Plan card.

+

A set of Apex Charts can also be created to see graphically what Predbat plans to do - Creating the charts.

+

Basic status

+
    +
  • predbat.status - Gives the current status & errors and logs any changes that Predbat makes to your inverter
  • +
+

Baseline data

+

What your battery is expected to do with no changes made by Predbat:

+
    +
  • predbat.battery_hours_left - The number of hours left until your home battery is predicted to run out (stops at the maximum prediction time)
  • +
  • predbat.charge_limit - The current charge limit used for the scenario in %
  • +
  • predbat.charge_limit_kw - The current charge limit used for the scenario in kwH
  • +
  • predbat.duration - The duration of the prediction maximum in hours
  • +
  • predbat.load_energy - Predicted load energy in kWh
  • +
  • predbat.pv_energy - Predicted PV energy in kWh
  • +
  • predbat.export_energy - Predicted export energy in kWh
  • +
  • predbat.import_energy - Predicted import energy in kWh
  • +
  • predbat.import_energy_battery - Predicted import energy to charge your home battery in kWh
  • +
  • predbat.import_energy_house - Predicted import energy not provided by your home battery (flat battery or above maximum discharge rate)
  • +
  • predbat.soc_kw - Predicted state of charge (in kWh) at the end of the prediction, not very useful in itself, but holds all +minute by minute prediction data (in attributes) which can be charted with Apex Charts (or similar)
  • +
  • predbat.soc_min_kwh - The minimum battery level during the time period in kWh
  • +
  • predbat.metric - Predicted cost metric for the next simulated period (in pence). Also contains data for charting cost in attributes.
  • +
  • predbat.battery_power - Predicted battery power per minute, for charting
  • +
  • predbat.battery_cycle - Predicted battery cycle in kWh (total kWh processed)
  • +
  • predbat.pv_power - Predicted PV power per minute, for charting
  • +
  • predbat.grid_power - Predicted Grid power per minute, for charting
  • +
  • predbat.car_soc - Predicted car battery %
  • +
+

PV 10% baseline data

+

The calculated baseline results under PV 10% scenario:

+
    +
  • predbat.soc_kw_base10 - As soc_kw but using the 10% solar forecast, also holds minute by minute data (in attributes) to be charted
  • +
  • predbat.base10_pv_energy - Predicted PV 10% energy in kWh
  • +
  • predbat.base10_metric - Predicted cost for PV 10%
  • +
  • predbat.base10_export_energy- Predicted export energy for PV 10%
  • +
  • predbat.base10_load_energy - Predicted load energy for PV 10%
  • +
  • predbat.base10_import_energy- Predicted import energy for PV 10%
  • +
+

Best

+

When calculate_best is enabled a second set of entities are created for the simulation based on the best battery charge percentage:

+
    +
  • predbat.best_battery_hours_left - Number of hours left under best plan
  • +
  • predbat.best_export_energy - Predicted exports under best plan
  • +
  • predbat_best_import_energy - Predicted imports under best plan
  • +
  • predbat_best_load - Predicted best load energy
  • +
  • predbat.best_pv_energy - Predicted Best PV energy in kWh
  • +
  • predbat_best_import_energy_battery - Predicted imports to the battery under best SOC setting
  • +
  • predbat_best_import_energy_house - Predicted imports to the house under best SOC setting
  • +
  • predbat_soc_kw_best - Predicted best final state of charge (in kWh), holds minute by minute prediction data (in attributes) to be charted
  • +
  • predbat.soc_kw_best_h1 - Single data point for the predicted state of charge in 1 hours time (useful for calibration charts, predicted vs actual)
  • +
  • predbat.soc_kw_best_h8 - Single data point for the predicted state of charge in 8 hours time (useful for calibration charts, predicted vs actual)
  • +
  • predbat.soc_kw_best_h12 - Single data point for the predicted state of charge in 12 hours time (useful for calibration charts, predicted vs actual)
  • +
  • predbat_best_metric - The predicted cost if the proposed SOC % charge target is selected. Also contains data for charting cost in attributes.
  • +
  • predbat.best_charge_limit - Predicted best battery charge limit in percent
  • +
  • predbat.best_charge_limit_kw - Predicted best battery charge limit in kwH
  • +
  • predbat.best_discharge_limit - Predicted best battery discharge limit in percent (will be 0% when discharging or 100% when not)
  • +
  • predbat.best_discharge_limit_kw - Predicted best battery discharge limit in kwH
  • +
  • predbat.battery_power_best - Predicted best battery power per minute, for charting
  • +
  • predbat.battery_cycle_best - Predicted best battery cycle in kWh (total kWh processed)
  • +
  • predbat.pv_power_best - Predicted best PV power per minute, for charting
  • +
  • predbat.grid_power - Predicted best Grid power per minute, for charting
  • +
  • predbat.car_soc_best - Predicated car battery % in best plan
  • +
  • predbat.iboost_best - Gives the predicted energy going into the iBoost - for charter
  • +
  • input_number.iboost_today - Gives the amount of energy modelled into the diverter today, resets at 11:30pm each night. Increments in the day.
  • +
+

Best PV 10%

+

The calculated best results under PV 10% scenario:

+
    +
  • predbat.soc_kw_best10 - As soc_kw_best but using the 10% solar forecast, also holds minute by minute data (in attributes) to be charted
  • +
  • predbat.best10_pv_energy - Predicted best PV 10% energy in kWh
  • +
  • predbat.best10_metric - Predicted best cost for PV 10%
  • +
  • predbat.best10_export_energy- Predicted best export energy for PV 10%
  • +
  • predbat.best10_load_energy - Predicted best load energy for PV 10%
  • +
  • predbat.best10_import_energy- Predicted best import energy for PV 10%
  • +
+

Energy rate data

+

Low import rate entities

+
    +
  • predbat.low_rate_cost - The lowest import rate cost in P
  • +
  • predbat.low_rate_start - Start time of the next low import rate
  • +
  • predbat.low_rate_end - End time of the next low import rate
  • +
  • predbat.low_rate_cost_2, predbat.low_rate_start_2, predbat.low_rate_end_2 - The following low import rate slot
  • +
  • binary_sensor.predbat_low_rate_slot - A sensor that indicates which there is a low energy rate slot active
  • +
+

High export rate entities

+
    +
  • predbat.high_export_rate_cost - The highest rate cost in P
  • +
  • predbat.high_export_rate_start - Start time of the next high export rate
  • +
  • predbat.high_export_rate_end - End time of the next high export rate
  • +
  • predbat.high_export_rate_cost_2, predbat.high_export_rate_start_2, predbat.high_export_rate_end_2 - The following high export rate slot
  • +
  • binary_sensor.predbat_high_export_rate_slot - A sensor that indicates which there is a high export rate slot active
  • +
+

Other rate entities

+
    +
  • predbat.rates - The current energy rates in P (also can be charted)
  • +
  • predbat.rates_export - The current energy export rates in P (also be be charted)
  • +
  • predbat.cost_today - The total cost of energy so far today (since midnight)
  • +
  • predbat.car_soc - The expected charge level of your car at the end of the simulation. Can also be charted.
  • +
  • predbat.car_soc_best - The expected charge level of your car at the end of the simulation using the proposed SOC%/Window. Can also be charted.
  • +
+

Car data

+
    +
  • binary_sensor.predbat_car_charging_slot - A binary sensor suggesting when to charge your car (if the car planning is enabled)
  • +
+

Sample Predbat data out dashboard

+

image

+

Predbat Logfile

+

Predbat writes detailed logging, status and progress activity information to a logfile as it runs and so this file should be checked if predbat.status reports an error, +or if you want to verify that Predbat is running OK.

+

There is a lot of output in the logfile, this is normal!

+

Depending upon whether you have used the combined AppDaemon/Predbat add-on installation method or the +HACS, Appdaemon add-on then Predbat installation method, the logfile will be held in one of two directories in Home Assistant:

+
    +
  • /addon_configs/46f69597_appdaemon-predbat/predbat.log if you used the combined AppDaemon/Predbat add-on installation method
  • +
+

or

+
    +
  • /homeassistant/appdaemon/appdaemon.log if you used the HACS, AppDaemon add-on then Predbat installation method
  • +
+

You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) +to view Predbat's logfile - see editing configuration files within Home Assistant if you need to install an editor.

+

Automated monitoring that Predbat and GivTCP are running OK

+

With GivTCP and Predbat performing an important function, managing your battery charging and discharging to best reduce your electricity bills, +you may find these automations useful to monitor that GivTCP and Predbat are running OK, and if not, to raise an alert on your mobile device.

+

GivTCP activity monitor

+

This automation will raise an alert if any of the following occur:

+
    +
  • The inverter goes offline for more than 30 minutes
  • +
  • No last_updated_time received from the inverter for more than 30 minutes
  • +
  • The battery goes offline to the inverter for more than 30 minutes
  • +
+

The script will need to be customised for your inverter id, battery id and mobile details, and can be extended for multiple inverters and batteries.

+
alias: GivTCP activity monitor
+description: Alert when communications to GivTCP have ceased for 30 minutes
+trigger:
+  - platform: state
+    entity_id: sensor.givtcp_<inverter id>_last_updated_time
+    to: null
+    for:
+      minutes: 30
+    id: no-givtcp-update
+    variables:
+      inv_id: inverter <id>
+  - platform: state
+    entity_id:
+      - sensor.givtcp_<inverter id>_status
+    from: online
+    for:
+      minutes: 30
+    id: no-givtcp-update
+    variables:
+      inv_id: inverter <id>
+  - platform: state
+    entity_id:
+      - sensor.givtcp_<battery id>_battery_cells
+    to: unknown
+    for:
+      minutes: 30
+    id: battery-unavailable
+    variables:
+      batt_id: <batt size/id>
+action:
+  - condition: trigger
+    id:
+      - no-givtcp-update
+  - service: notify.mobile_app_<your mobile device id>
+    data:
+      title: GivTCP communication issue
+      message: |
+        {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE:
+        No GivTCP update received from {{ inv_id }} for the past 30 minutes.
+      data:
+        visibility: public
+        persistent: true
+        push:
+          sound:
+            name: default
+            critical: 1
+            volume: 0.8
+        sticky: true
+        color: red
+  - condition: trigger
+    id:
+      - battery-unavailable
+  - service: notify.mobile_app_<your mobile device id>
+    data:
+      title: GivTCP communication issue
+      message: |
+        {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE:
+        Battery {{ batt_id }} offline to GivTCP for the past 30 minutes.
+      data:
+        visibility: public
+        persistent: true
+        push:
+          sound:
+            name: default
+            critical: 1
+            volume: 0.8
+        sticky: true
+        color: red
+mode: single
+
+

Predbat error monitor

+

This automation will raise an alert if Predbat's status turns to ERROR for more than 10 minutes.

+

The script will need to be customised for your mobile details.

+
alias: predbat error monitor
+description: Alert when Predbat has raised an exception
+trigger:
+  - platform: state
+    entity_id:
+      - predbat.status
+    to: "ERROR: Exception raised"
+    for:
+      minutes: 10
+  - platform: template
+    value_template: "{{ 'ERROR' in states('predbat.status') }}"
+    for:
+      minutes: 10
+action:
+  - service: notify.mobile_app_<your mobile device id>
+    data:
+      title: Predbat status issue
+      message: |
+        {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE:
+        predbat status is {{ states('predbat.status') }}
+      data:
+        visibility: public
+        persistent: true
+        push:
+          sound:
+            name: default
+            critical: 1
+            volume: 0.8
+        sticky: true
+        color: red
+mode: single
+
+

An error alert looks like this:

+

image

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/predbat-plan-card/index.html b/predbat-plan-card/index.html new file mode 100644 index 000000000..1fa9a1af0 --- /dev/null +++ b/predbat-plan-card/index.html @@ -0,0 +1,179 @@ + + + + + + + + Predbat Plan card - Predbat Documentation + + + + + + + + + + + + + +
+ + +
+ +
+
+
    +
  • + + +
  • +
  • +
+
+
+
+
+ +

Predbat Plan card

+

Predbat can create its own plan card which can be added to your HA dashboard.

+ +

Next create a new card as follows:

+
type: custom:html-template-card
+title: Predbat plan
+ignore_line_breaks: true
+content: |
+  {{ state_attr('predbat.plan_html', 'html') }}
+
+

You should see something like this:

+

image

+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
+ + + + + + + + + diff --git a/search.html b/search.html new file mode 100644 index 000000000..fca33f3a3 --- /dev/null +++ b/search.html @@ -0,0 +1,155 @@ + + + + + + + + Predbat Documentation + + + + + + + + + + + +
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+ + + + + + + + + diff --git a/search/lunr.js b/search/lunr.js new file mode 100644 index 000000000..aca0a167f --- /dev/null +++ b/search/lunr.js @@ -0,0 +1,3475 @@ +/** + * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9 + * Copyright (C) 2020 Oliver Nightingale + * @license MIT + */ + +;(function(){ + +/** + * A convenience function for configuring and constructing + * a new lunr Index. + * + * A lunr.Builder instance is created and the pipeline setup + * with a trimmer, stop word filter and stemmer. + * + * This builder object is yielded to the configuration function + * that is passed as a parameter, allowing the list of fields + * and other builder parameters to be customised. + * + * All documents _must_ be added within the passed config function. + * + * @example + * var idx = lunr(function () { + * this.field('title') + * this.field('body') + * this.ref('id') + * + * documents.forEach(function (doc) { + * this.add(doc) + * }, this) + * }) + * + * @see {@link lunr.Builder} + * @see {@link lunr.Pipeline} + * @see {@link lunr.trimmer} + * @see {@link lunr.stopWordFilter} + * @see {@link lunr.stemmer} + * @namespace {function} lunr + */ +var lunr = function (config) { + var builder = new lunr.Builder + + builder.pipeline.add( + lunr.trimmer, + lunr.stopWordFilter, + lunr.stemmer + ) + + builder.searchPipeline.add( + lunr.stemmer + ) + + config.call(builder, builder) + return builder.build() +} + +lunr.version = "2.3.9" +/*! + * lunr.utils + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A namespace containing utils for the rest of the lunr library + * @namespace lunr.utils + */ +lunr.utils = {} + +/** + * Print a warning message to the console. + * + * @param {String} message The message to be printed. + * @memberOf lunr.utils + * @function + */ +lunr.utils.warn = (function (global) { + /* eslint-disable no-console */ + return function (message) { + if (global.console && console.warn) { + console.warn(message) + } + } + /* eslint-enable no-console */ +})(this) + +/** + * Convert an object to a string. + * + * In the case of `null` and `undefined` the function returns + * the empty string, in all other cases the result of calling + * `toString` on the passed object is returned. + * + * @param {Any} obj The object to convert to a string. + * @return {String} string representation of the passed object. + * @memberOf lunr.utils + */ +lunr.utils.asString = function (obj) { + if (obj === void 0 || obj === null) { + return "" + } else { + return obj.toString() + } +} + +/** + * Clones an object. + * + * Will create a copy of an existing object such that any mutations + * on the copy cannot affect the original. + * + * Only shallow objects are supported, passing a nested object to this + * function will cause a TypeError. + * + * Objects with primitives, and arrays of primitives are supported. + * + * @param {Object} obj The object to clone. + * @return {Object} a clone of the passed object. + * @throws {TypeError} when a nested object is passed. + * @memberOf Utils + */ +lunr.utils.clone = function (obj) { + if (obj === null || obj === undefined) { + return obj + } + + var clone = Object.create(null), + keys = Object.keys(obj) + + for (var i = 0; i < keys.length; i++) { + var key = keys[i], + val = obj[key] + + if (Array.isArray(val)) { + clone[key] = val.slice() + continue + } + + if (typeof val === 'string' || + typeof val === 'number' || + typeof val === 'boolean') { + clone[key] = val + continue + } + + throw new TypeError("clone is not deep and does not support nested objects") + } + + return clone +} +lunr.FieldRef = function (docRef, fieldName, stringValue) { + this.docRef = docRef + this.fieldName = fieldName + this._stringValue = stringValue +} + +lunr.FieldRef.joiner = "/" + +lunr.FieldRef.fromString = function (s) { + var n = s.indexOf(lunr.FieldRef.joiner) + + if (n === -1) { + throw "malformed field ref string" + } + + var fieldRef = s.slice(0, n), + docRef = s.slice(n + 1) + + return new lunr.FieldRef (docRef, fieldRef, s) +} + +lunr.FieldRef.prototype.toString = function () { + if (this._stringValue == undefined) { + this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef + } + + return this._stringValue +} +/*! + * lunr.Set + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A lunr set. + * + * @constructor + */ +lunr.Set = function (elements) { + this.elements = Object.create(null) + + if (elements) { + this.length = elements.length + + for (var i = 0; i < this.length; i++) { + this.elements[elements[i]] = true + } + } else { + this.length = 0 + } +} + +/** + * A complete set that contains all elements. + * + * @static + * @readonly + * @type {lunr.Set} + */ +lunr.Set.complete = { + intersect: function (other) { + return other + }, + + union: function () { + return this + }, + + contains: function () { + return true + } +} + +/** + * An empty set that contains no elements. + * + * @static + * @readonly + * @type {lunr.Set} + */ +lunr.Set.empty = { + intersect: function () { + return this + }, + + union: function (other) { + return other + }, + + contains: function () { + return false + } +} + +/** + * Returns true if this set contains the specified object. + * + * @param {object} object - Object whose presence in this set is to be tested. + * @returns {boolean} - True if this set contains the specified object. + */ +lunr.Set.prototype.contains = function (object) { + return !!this.elements[object] +} + +/** + * Returns a new set containing only the elements that are present in both + * this set and the specified set. + * + * @param {lunr.Set} other - set to intersect with this set. + * @returns {lunr.Set} a new set that is the intersection of this and the specified set. + */ + +lunr.Set.prototype.intersect = function (other) { + var a, b, elements, intersection = [] + + if (other === lunr.Set.complete) { + return this + } + + if (other === lunr.Set.empty) { + return other + } + + if (this.length < other.length) { + a = this + b = other + } else { + a = other + b = this + } + + elements = Object.keys(a.elements) + + for (var i = 0; i < elements.length; i++) { + var element = elements[i] + if (element in b.elements) { + intersection.push(element) + } + } + + return new lunr.Set (intersection) +} + +/** + * Returns a new set combining the elements of this and the specified set. + * + * @param {lunr.Set} other - set to union with this set. + * @return {lunr.Set} a new set that is the union of this and the specified set. + */ + +lunr.Set.prototype.union = function (other) { + if (other === lunr.Set.complete) { + return lunr.Set.complete + } + + if (other === lunr.Set.empty) { + return this + } + + return new lunr.Set(Object.keys(this.elements).concat(Object.keys(other.elements))) +} +/** + * A function to calculate the inverse document frequency for + * a posting. This is shared between the builder and the index + * + * @private + * @param {object} posting - The posting for a given term + * @param {number} documentCount - The total number of documents. + */ +lunr.idf = function (posting, documentCount) { + var documentsWithTerm = 0 + + for (var fieldName in posting) { + if (fieldName == '_index') continue // Ignore the term index, its not a field + documentsWithTerm += Object.keys(posting[fieldName]).length + } + + var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5) + + return Math.log(1 + Math.abs(x)) +} + +/** + * A token wraps a string representation of a token + * as it is passed through the text processing pipeline. + * + * @constructor + * @param {string} [str=''] - The string token being wrapped. + * @param {object} [metadata={}] - Metadata associated with this token. + */ +lunr.Token = function (str, metadata) { + this.str = str || "" + this.metadata = metadata || {} +} + +/** + * Returns the token string that is being wrapped by this object. + * + * @returns {string} + */ +lunr.Token.prototype.toString = function () { + return this.str +} + +/** + * A token update function is used when updating or optionally + * when cloning a token. + * + * @callback lunr.Token~updateFunction + * @param {string} str - The string representation of the token. + * @param {Object} metadata - All metadata associated with this token. + */ + +/** + * Applies the given function to the wrapped string token. + * + * @example + * token.update(function (str, metadata) { + * return str.toUpperCase() + * }) + * + * @param {lunr.Token~updateFunction} fn - A function to apply to the token string. + * @returns {lunr.Token} + */ +lunr.Token.prototype.update = function (fn) { + this.str = fn(this.str, this.metadata) + return this +} + +/** + * Creates a clone of this token. Optionally a function can be + * applied to the cloned token. + * + * @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token. + * @returns {lunr.Token} + */ +lunr.Token.prototype.clone = function (fn) { + fn = fn || function (s) { return s } + return new lunr.Token (fn(this.str, this.metadata), this.metadata) +} +/*! + * lunr.tokenizer + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A function for splitting a string into tokens ready to be inserted into + * the search index. Uses `lunr.tokenizer.separator` to split strings, change + * the value of this property to change how strings are split into tokens. + * + * This tokenizer will convert its parameter to a string by calling `toString` and + * then will split this string on the character in `lunr.tokenizer.separator`. + * Arrays will have their elements converted to strings and wrapped in a lunr.Token. + * + * Optional metadata can be passed to the tokenizer, this metadata will be cloned and + * added as metadata to every token that is created from the object to be tokenized. + * + * @static + * @param {?(string|object|object[])} obj - The object to convert into tokens + * @param {?object} metadata - Optional metadata to associate with every token + * @returns {lunr.Token[]} + * @see {@link lunr.Pipeline} + */ +lunr.tokenizer = function (obj, metadata) { + if (obj == null || obj == undefined) { + return [] + } + + if (Array.isArray(obj)) { + return obj.map(function (t) { + return new lunr.Token( + lunr.utils.asString(t).toLowerCase(), + lunr.utils.clone(metadata) + ) + }) + } + + var str = obj.toString().toLowerCase(), + len = str.length, + tokens = [] + + for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) { + var char = str.charAt(sliceEnd), + sliceLength = sliceEnd - sliceStart + + if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) { + + if (sliceLength > 0) { + var tokenMetadata = lunr.utils.clone(metadata) || {} + tokenMetadata["position"] = [sliceStart, sliceLength] + tokenMetadata["index"] = tokens.length + + tokens.push( + new lunr.Token ( + str.slice(sliceStart, sliceEnd), + tokenMetadata + ) + ) + } + + sliceStart = sliceEnd + 1 + } + + } + + return tokens +} + +/** + * The separator used to split a string into tokens. Override this property to change the behaviour of + * `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens. + * + * @static + * @see lunr.tokenizer + */ +lunr.tokenizer.separator = /[\s\-]+/ +/*! + * lunr.Pipeline + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.Pipelines maintain an ordered list of functions to be applied to all + * tokens in documents entering the search index and queries being ran against + * the index. + * + * An instance of lunr.Index created with the lunr shortcut will contain a + * pipeline with a stop word filter and an English language stemmer. Extra + * functions can be added before or after either of these functions or these + * default functions can be removed. + * + * When run the pipeline will call each function in turn, passing a token, the + * index of that token in the original list of all tokens and finally a list of + * all the original tokens. + * + * The output of functions in the pipeline will be passed to the next function + * in the pipeline. To exclude a token from entering the index the function + * should return undefined, the rest of the pipeline will not be called with + * this token. + * + * For serialisation of pipelines to work, all functions used in an instance of + * a pipeline should be registered with lunr.Pipeline. Registered functions can + * then be loaded. If trying to load a serialised pipeline that uses functions + * that are not registered an error will be thrown. + * + * If not planning on serialising the pipeline then registering pipeline functions + * is not necessary. + * + * @constructor + */ +lunr.Pipeline = function () { + this._stack = [] +} + +lunr.Pipeline.registeredFunctions = Object.create(null) + +/** + * A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token + * string as well as all known metadata. A pipeline function can mutate the token string + * or mutate (or add) metadata for a given token. + * + * A pipeline function can indicate that the passed token should be discarded by returning + * null, undefined or an empty string. This token will not be passed to any downstream pipeline + * functions and will not be added to the index. + * + * Multiple tokens can be returned by returning an array of tokens. Each token will be passed + * to any downstream pipeline functions and all will returned tokens will be added to the index. + * + * Any number of pipeline functions may be chained together using a lunr.Pipeline. + * + * @interface lunr.PipelineFunction + * @param {lunr.Token} token - A token from the document being processed. + * @param {number} i - The index of this token in the complete list of tokens for this document/field. + * @param {lunr.Token[]} tokens - All tokens for this document/field. + * @returns {(?lunr.Token|lunr.Token[])} + */ + +/** + * Register a function with the pipeline. + * + * Functions that are used in the pipeline should be registered if the pipeline + * needs to be serialised, or a serialised pipeline needs to be loaded. + * + * Registering a function does not add it to a pipeline, functions must still be + * added to instances of the pipeline for them to be used when running a pipeline. + * + * @param {lunr.PipelineFunction} fn - The function to check for. + * @param {String} label - The label to register this function with + */ +lunr.Pipeline.registerFunction = function (fn, label) { + if (label in this.registeredFunctions) { + lunr.utils.warn('Overwriting existing registered function: ' + label) + } + + fn.label = label + lunr.Pipeline.registeredFunctions[fn.label] = fn +} + +/** + * Warns if the function is not registered as a Pipeline function. + * + * @param {lunr.PipelineFunction} fn - The function to check for. + * @private + */ +lunr.Pipeline.warnIfFunctionNotRegistered = function (fn) { + var isRegistered = fn.label && (fn.label in this.registeredFunctions) + + if (!isRegistered) { + lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\n', fn) + } +} + +/** + * Loads a previously serialised pipeline. + * + * All functions to be loaded must already be registered with lunr.Pipeline. + * If any function from the serialised data has not been registered then an + * error will be thrown. + * + * @param {Object} serialised - The serialised pipeline to load. + * @returns {lunr.Pipeline} + */ +lunr.Pipeline.load = function (serialised) { + var pipeline = new lunr.Pipeline + + serialised.forEach(function (fnName) { + var fn = lunr.Pipeline.registeredFunctions[fnName] + + if (fn) { + pipeline.add(fn) + } else { + throw new Error('Cannot load unregistered function: ' + fnName) + } + }) + + return pipeline +} + +/** + * Adds new functions to the end of the pipeline. + * + * Logs a warning if the function has not been registered. + * + * @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline. + */ +lunr.Pipeline.prototype.add = function () { + var fns = Array.prototype.slice.call(arguments) + + fns.forEach(function (fn) { + lunr.Pipeline.warnIfFunctionNotRegistered(fn) + this._stack.push(fn) + }, this) +} + +/** + * Adds a single function after a function that already exists in the + * pipeline. + * + * Logs a warning if the function has not been registered. + * + * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline. + * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline. + */ +lunr.Pipeline.prototype.after = function (existingFn, newFn) { + lunr.Pipeline.warnIfFunctionNotRegistered(newFn) + + var pos = this._stack.indexOf(existingFn) + if (pos == -1) { + throw new Error('Cannot find existingFn') + } + + pos = pos + 1 + this._stack.splice(pos, 0, newFn) +} + +/** + * Adds a single function before a function that already exists in the + * pipeline. + * + * Logs a warning if the function has not been registered. + * + * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline. + * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline. + */ +lunr.Pipeline.prototype.before = function (existingFn, newFn) { + lunr.Pipeline.warnIfFunctionNotRegistered(newFn) + + var pos = this._stack.indexOf(existingFn) + if (pos == -1) { + throw new Error('Cannot find existingFn') + } + + this._stack.splice(pos, 0, newFn) +} + +/** + * Removes a function from the pipeline. + * + * @param {lunr.PipelineFunction} fn The function to remove from the pipeline. + */ +lunr.Pipeline.prototype.remove = function (fn) { + var pos = this._stack.indexOf(fn) + if (pos == -1) { + return + } + + this._stack.splice(pos, 1) +} + +/** + * Runs the current list of functions that make up the pipeline against the + * passed tokens. + * + * @param {Array} tokens The tokens to run through the pipeline. + * @returns {Array} + */ +lunr.Pipeline.prototype.run = function (tokens) { + var stackLength = this._stack.length + + for (var i = 0; i < stackLength; i++) { + var fn = this._stack[i] + var memo = [] + + for (var j = 0; j < tokens.length; j++) { + var result = fn(tokens[j], j, tokens) + + if (result === null || result === void 0 || result === '') continue + + if (Array.isArray(result)) { + for (var k = 0; k < result.length; k++) { + memo.push(result[k]) + } + } else { + memo.push(result) + } + } + + tokens = memo + } + + return tokens +} + +/** + * Convenience method for passing a string through a pipeline and getting + * strings out. This method takes care of wrapping the passed string in a + * token and mapping the resulting tokens back to strings. + * + * @param {string} str - The string to pass through the pipeline. + * @param {?object} metadata - Optional metadata to associate with the token + * passed to the pipeline. + * @returns {string[]} + */ +lunr.Pipeline.prototype.runString = function (str, metadata) { + var token = new lunr.Token (str, metadata) + + return this.run([token]).map(function (t) { + return t.toString() + }) +} + +/** + * Resets the pipeline by removing any existing processors. + * + */ +lunr.Pipeline.prototype.reset = function () { + this._stack = [] +} + +/** + * Returns a representation of the pipeline ready for serialisation. + * + * Logs a warning if the function has not been registered. + * + * @returns {Array} + */ +lunr.Pipeline.prototype.toJSON = function () { + return this._stack.map(function (fn) { + lunr.Pipeline.warnIfFunctionNotRegistered(fn) + + return fn.label + }) +} +/*! + * lunr.Vector + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A vector is used to construct the vector space of documents and queries. These + * vectors support operations to determine the similarity between two documents or + * a document and a query. + * + * Normally no parameters are required for initializing a vector, but in the case of + * loading a previously dumped vector the raw elements can be provided to the constructor. + * + * For performance reasons vectors are implemented with a flat array, where an elements + * index is immediately followed by its value. E.g. [index, value, index, value]. This + * allows the underlying array to be as sparse as possible and still offer decent + * performance when being used for vector calculations. + * + * @constructor + * @param {Number[]} [elements] - The flat list of element index and element value pairs. + */ +lunr.Vector = function (elements) { + this._magnitude = 0 + this.elements = elements || [] +} + + +/** + * Calculates the position within the vector to insert a given index. + * + * This is used internally by insert and upsert. If there are duplicate indexes then + * the position is returned as if the value for that index were to be updated, but it + * is the callers responsibility to check whether there is a duplicate at that index + * + * @param {Number} insertIdx - The index at which the element should be inserted. + * @returns {Number} + */ +lunr.Vector.prototype.positionForIndex = function (index) { + // For an empty vector the tuple can be inserted at the beginning + if (this.elements.length == 0) { + return 0 + } + + var start = 0, + end = this.elements.length / 2, + sliceLength = end - start, + pivotPoint = Math.floor(sliceLength / 2), + pivotIndex = this.elements[pivotPoint * 2] + + while (sliceLength > 1) { + if (pivotIndex < index) { + start = pivotPoint + } + + if (pivotIndex > index) { + end = pivotPoint + } + + if (pivotIndex == index) { + break + } + + sliceLength = end - start + pivotPoint = start + Math.floor(sliceLength / 2) + pivotIndex = this.elements[pivotPoint * 2] + } + + if (pivotIndex == index) { + return pivotPoint * 2 + } + + if (pivotIndex > index) { + return pivotPoint * 2 + } + + if (pivotIndex < index) { + return (pivotPoint + 1) * 2 + } +} + +/** + * Inserts an element at an index within the vector. + * + * Does not allow duplicates, will throw an error if there is already an entry + * for this index. + * + * @param {Number} insertIdx - The index at which the element should be inserted. + * @param {Number} val - The value to be inserted into the vector. + */ +lunr.Vector.prototype.insert = function (insertIdx, val) { + this.upsert(insertIdx, val, function () { + throw "duplicate index" + }) +} + +/** + * Inserts or updates an existing index within the vector. + * + * @param {Number} insertIdx - The index at which the element should be inserted. + * @param {Number} val - The value to be inserted into the vector. + * @param {function} fn - A function that is called for updates, the existing value and the + * requested value are passed as arguments + */ +lunr.Vector.prototype.upsert = function (insertIdx, val, fn) { + this._magnitude = 0 + var position = this.positionForIndex(insertIdx) + + if (this.elements[position] == insertIdx) { + this.elements[position + 1] = fn(this.elements[position + 1], val) + } else { + this.elements.splice(position, 0, insertIdx, val) + } +} + +/** + * Calculates the magnitude of this vector. + * + * @returns {Number} + */ +lunr.Vector.prototype.magnitude = function () { + if (this._magnitude) return this._magnitude + + var sumOfSquares = 0, + elementsLength = this.elements.length + + for (var i = 1; i < elementsLength; i += 2) { + var val = this.elements[i] + sumOfSquares += val * val + } + + return this._magnitude = Math.sqrt(sumOfSquares) +} + +/** + * Calculates the dot product of this vector and another vector. + * + * @param {lunr.Vector} otherVector - The vector to compute the dot product with. + * @returns {Number} + */ +lunr.Vector.prototype.dot = function (otherVector) { + var dotProduct = 0, + a = this.elements, b = otherVector.elements, + aLen = a.length, bLen = b.length, + aVal = 0, bVal = 0, + i = 0, j = 0 + + while (i < aLen && j < bLen) { + aVal = a[i], bVal = b[j] + if (aVal < bVal) { + i += 2 + } else if (aVal > bVal) { + j += 2 + } else if (aVal == bVal) { + dotProduct += a[i + 1] * b[j + 1] + i += 2 + j += 2 + } + } + + return dotProduct +} + +/** + * Calculates the similarity between this vector and another vector. + * + * @param {lunr.Vector} otherVector - The other vector to calculate the + * similarity with. + * @returns {Number} + */ +lunr.Vector.prototype.similarity = function (otherVector) { + return this.dot(otherVector) / this.magnitude() || 0 +} + +/** + * Converts the vector to an array of the elements within the vector. + * + * @returns {Number[]} + */ +lunr.Vector.prototype.toArray = function () { + var output = new Array (this.elements.length / 2) + + for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) { + output[j] = this.elements[i] + } + + return output +} + +/** + * A JSON serializable representation of the vector. + * + * @returns {Number[]} + */ +lunr.Vector.prototype.toJSON = function () { + return this.elements +} +/* eslint-disable */ +/*! + * lunr.stemmer + * Copyright (C) 2020 Oliver Nightingale + * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt + */ + +/** + * lunr.stemmer is an english language stemmer, this is a JavaScript + * implementation of the PorterStemmer taken from http://tartarus.org/~martin + * + * @static + * @implements {lunr.PipelineFunction} + * @param {lunr.Token} token - The string to stem + * @returns {lunr.Token} + * @see {@link lunr.Pipeline} + * @function + */ +lunr.stemmer = (function(){ + var step2list = { + "ational" : "ate", + "tional" : "tion", + "enci" : "ence", + "anci" : "ance", + "izer" : "ize", + "bli" : "ble", + "alli" : "al", + "entli" : "ent", + "eli" : "e", + "ousli" : "ous", + "ization" : "ize", + "ation" : "ate", + "ator" : "ate", + "alism" : "al", + "iveness" : "ive", + "fulness" : "ful", + "ousness" : "ous", + "aliti" : "al", + "iviti" : "ive", + "biliti" : "ble", + "logi" : "log" + }, + + step3list = { + "icate" : "ic", + "ative" : "", + "alize" : "al", + "iciti" : "ic", + "ical" : "ic", + "ful" : "", + "ness" : "" + }, + + c = "[^aeiou]", // consonant + v = "[aeiouy]", // vowel + C = c + "[^aeiouy]*", // consonant sequence + V = v + "[aeiou]*", // vowel sequence + + mgr0 = "^(" + C + ")?" + V + C, // [C]VC... is m>0 + meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$", // [C]VC[V] is m=1 + mgr1 = "^(" + C + ")?" + V + C + V + C, // [C]VCVC... is m>1 + s_v = "^(" + C + ")?" + v; // vowel in stem + + var re_mgr0 = new RegExp(mgr0); + var re_mgr1 = new RegExp(mgr1); + var re_meq1 = new RegExp(meq1); + var re_s_v = new RegExp(s_v); + + var re_1a = /^(.+?)(ss|i)es$/; + var re2_1a = /^(.+?)([^s])s$/; + var re_1b = /^(.+?)eed$/; + var re2_1b = /^(.+?)(ed|ing)$/; + var re_1b_2 = /.$/; + var re2_1b_2 = /(at|bl|iz)$/; + var re3_1b_2 = new RegExp("([^aeiouylsz])\\1$"); + var re4_1b_2 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + + var re_1c = /^(.+?[^aeiou])y$/; + var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + + var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + + var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + var re2_4 = /^(.+?)(s|t)(ion)$/; + + var re_5 = /^(.+?)e$/; + var re_5_1 = /ll$/; + var re3_5 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + + var porterStemmer = function porterStemmer(w) { + var stem, + suffix, + firstch, + re, + re2, + re3, + re4; + + if (w.length < 3) { return w; } + + firstch = w.substr(0,1); + if (firstch == "y") { + w = firstch.toUpperCase() + w.substr(1); + } + + // Step 1a + re = re_1a + re2 = re2_1a; + + if (re.test(w)) { w = w.replace(re,"$1$2"); } + else if (re2.test(w)) { w = w.replace(re2,"$1$2"); } + + // Step 1b + re = re_1b; + re2 = re2_1b; + if (re.test(w)) { + var fp = re.exec(w); + re = re_mgr0; + if (re.test(fp[1])) { + re = re_1b_2; + w = w.replace(re,""); + } + } else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = re_s_v; + if (re2.test(stem)) { + w = stem; + re2 = re2_1b_2; + re3 = re3_1b_2; + re4 = re4_1b_2; + if (re2.test(w)) { w = w + "e"; } + else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,""); } + else if (re4.test(w)) { w = w + "e"; } + } + } + + // Step 1c - replace suffix y or Y by i if preceded by a non-vowel which is not the first letter of the word (so cry -> cri, by -> by, say -> say) + re = re_1c; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + w = stem + "i"; + } + + // Step 2 + re = re_2; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = re_mgr0; + if (re.test(stem)) { + w = stem + step2list[suffix]; + } + } + + // Step 3 + re = re_3; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = re_mgr0; + if (re.test(stem)) { + w = stem + step3list[suffix]; + } + } + + // Step 4 + re = re_4; + re2 = re2_4; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = re_mgr1; + if (re.test(stem)) { + w = stem; + } + } else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1] + fp[2]; + re2 = re_mgr1; + if (re2.test(stem)) { + w = stem; + } + } + + // Step 5 + re = re_5; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = re_mgr1; + re2 = re_meq1; + re3 = re3_5; + if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) { + w = stem; + } + } + + re = re_5_1; + re2 = re_mgr1; + if (re.test(w) && re2.test(w)) { + re = re_1b_2; + w = w.replace(re,""); + } + + // and turn initial Y back to y + + if (firstch == "y") { + w = firstch.toLowerCase() + w.substr(1); + } + + return w; + }; + + return function (token) { + return token.update(porterStemmer); + } +})(); + +lunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer') +/*! + * lunr.stopWordFilter + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.generateStopWordFilter builds a stopWordFilter function from the provided + * list of stop words. + * + * The built in lunr.stopWordFilter is built using this generator and can be used + * to generate custom stopWordFilters for applications or non English languages. + * + * @function + * @param {Array} token The token to pass through the filter + * @returns {lunr.PipelineFunction} + * @see lunr.Pipeline + * @see lunr.stopWordFilter + */ +lunr.generateStopWordFilter = function (stopWords) { + var words = stopWords.reduce(function (memo, stopWord) { + memo[stopWord] = stopWord + return memo + }, {}) + + return function (token) { + if (token && words[token.toString()] !== token.toString()) return token + } +} + +/** + * lunr.stopWordFilter is an English language stop word list filter, any words + * contained in the list will not be passed through the filter. + * + * This is intended to be used in the Pipeline. If the token does not pass the + * filter then undefined will be returned. + * + * @function + * @implements {lunr.PipelineFunction} + * @params {lunr.Token} token - A token to check for being a stop word. + * @returns {lunr.Token} + * @see {@link lunr.Pipeline} + */ +lunr.stopWordFilter = lunr.generateStopWordFilter([ + 'a', + 'able', + 'about', + 'across', + 'after', + 'all', + 'almost', + 'also', + 'am', + 'among', + 'an', + 'and', + 'any', + 'are', + 'as', + 'at', + 'be', + 'because', + 'been', + 'but', + 'by', + 'can', + 'cannot', + 'could', + 'dear', + 'did', + 'do', + 'does', + 'either', + 'else', + 'ever', + 'every', + 'for', + 'from', + 'get', + 'got', + 'had', + 'has', + 'have', + 'he', + 'her', + 'hers', + 'him', + 'his', + 'how', + 'however', + 'i', + 'if', + 'in', + 'into', + 'is', + 'it', + 'its', + 'just', + 'least', + 'let', + 'like', + 'likely', + 'may', + 'me', + 'might', + 'most', + 'must', + 'my', + 'neither', + 'no', + 'nor', + 'not', + 'of', + 'off', + 'often', + 'on', + 'only', + 'or', + 'other', + 'our', + 'own', + 'rather', + 'said', + 'say', + 'says', + 'she', + 'should', + 'since', + 'so', + 'some', + 'than', + 'that', + 'the', + 'their', + 'them', + 'then', + 'there', + 'these', + 'they', + 'this', + 'tis', + 'to', + 'too', + 'twas', + 'us', + 'wants', + 'was', + 'we', + 'were', + 'what', + 'when', + 'where', + 'which', + 'while', + 'who', + 'whom', + 'why', + 'will', + 'with', + 'would', + 'yet', + 'you', + 'your' +]) + +lunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter') +/*! + * lunr.trimmer + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.trimmer is a pipeline function for trimming non word + * characters from the beginning and end of tokens before they + * enter the index. + * + * This implementation may not work correctly for non latin + * characters and should either be removed or adapted for use + * with languages with non-latin characters. + * + * @static + * @implements {lunr.PipelineFunction} + * @param {lunr.Token} token The token to pass through the filter + * @returns {lunr.Token} + * @see lunr.Pipeline + */ +lunr.trimmer = function (token) { + return token.update(function (s) { + return s.replace(/^\W+/, '').replace(/\W+$/, '') + }) +} + +lunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer') +/*! + * lunr.TokenSet + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A token set is used to store the unique list of all tokens + * within an index. Token sets are also used to represent an + * incoming query to the index, this query token set and index + * token set are then intersected to find which tokens to look + * up in the inverted index. + * + * A token set can hold multiple tokens, as in the case of the + * index token set, or it can hold a single token as in the + * case of a simple query token set. + * + * Additionally token sets are used to perform wildcard matching. + * Leading, contained and trailing wildcards are supported, and + * from this edit distance matching can also be provided. + * + * Token sets are implemented as a minimal finite state automata, + * where both common prefixes and suffixes are shared between tokens. + * This helps to reduce the space used for storing the token set. + * + * @constructor + */ +lunr.TokenSet = function () { + this.final = false + this.edges = {} + this.id = lunr.TokenSet._nextId + lunr.TokenSet._nextId += 1 +} + +/** + * Keeps track of the next, auto increment, identifier to assign + * to a new tokenSet. + * + * TokenSets require a unique identifier to be correctly minimised. + * + * @private + */ +lunr.TokenSet._nextId = 1 + +/** + * Creates a TokenSet instance from the given sorted array of words. + * + * @param {String[]} arr - A sorted array of strings to create the set from. + * @returns {lunr.TokenSet} + * @throws Will throw an error if the input array is not sorted. + */ +lunr.TokenSet.fromArray = function (arr) { + var builder = new lunr.TokenSet.Builder + + for (var i = 0, len = arr.length; i < len; i++) { + builder.insert(arr[i]) + } + + builder.finish() + return builder.root +} + +/** + * Creates a token set from a query clause. + * + * @private + * @param {Object} clause - A single clause from lunr.Query. + * @param {string} clause.term - The query clause term. + * @param {number} [clause.editDistance] - The optional edit distance for the term. + * @returns {lunr.TokenSet} + */ +lunr.TokenSet.fromClause = function (clause) { + if ('editDistance' in clause) { + return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance) + } else { + return lunr.TokenSet.fromString(clause.term) + } +} + +/** + * Creates a token set representing a single string with a specified + * edit distance. + * + * Insertions, deletions, substitutions and transpositions are each + * treated as an edit distance of 1. + * + * Increasing the allowed edit distance will have a dramatic impact + * on the performance of both creating and intersecting these TokenSets. + * It is advised to keep the edit distance less than 3. + * + * @param {string} str - The string to create the token set from. + * @param {number} editDistance - The allowed edit distance to match. + * @returns {lunr.Vector} + */ +lunr.TokenSet.fromFuzzyString = function (str, editDistance) { + var root = new lunr.TokenSet + + var stack = [{ + node: root, + editsRemaining: editDistance, + str: str + }] + + while (stack.length) { + var frame = stack.pop() + + // no edit + if (frame.str.length > 0) { + var char = frame.str.charAt(0), + noEditNode + + if (char in frame.node.edges) { + noEditNode = frame.node.edges[char] + } else { + noEditNode = new lunr.TokenSet + frame.node.edges[char] = noEditNode + } + + if (frame.str.length == 1) { + noEditNode.final = true + } + + stack.push({ + node: noEditNode, + editsRemaining: frame.editsRemaining, + str: frame.str.slice(1) + }) + } + + if (frame.editsRemaining == 0) { + continue + } + + // insertion + if ("*" in frame.node.edges) { + var insertionNode = frame.node.edges["*"] + } else { + var insertionNode = new lunr.TokenSet + frame.node.edges["*"] = insertionNode + } + + if (frame.str.length == 0) { + insertionNode.final = true + } + + stack.push({ + node: insertionNode, + editsRemaining: frame.editsRemaining - 1, + str: frame.str + }) + + // deletion + // can only do a deletion if we have enough edits remaining + // and if there are characters left to delete in the string + if (frame.str.length > 1) { + stack.push({ + node: frame.node, + editsRemaining: frame.editsRemaining - 1, + str: frame.str.slice(1) + }) + } + + // deletion + // just removing the last character from the str + if (frame.str.length == 1) { + frame.node.final = true + } + + // substitution + // can only do a substitution if we have enough edits remaining + // and if there are characters left to substitute + if (frame.str.length >= 1) { + if ("*" in frame.node.edges) { + var substitutionNode = frame.node.edges["*"] + } else { + var substitutionNode = new lunr.TokenSet + frame.node.edges["*"] = substitutionNode + } + + if (frame.str.length == 1) { + substitutionNode.final = true + } + + stack.push({ + node: substitutionNode, + editsRemaining: frame.editsRemaining - 1, + str: frame.str.slice(1) + }) + } + + // transposition + // can only do a transposition if there are edits remaining + // and there are enough characters to transpose + if (frame.str.length > 1) { + var charA = frame.str.charAt(0), + charB = frame.str.charAt(1), + transposeNode + + if (charB in frame.node.edges) { + transposeNode = frame.node.edges[charB] + } else { + transposeNode = new lunr.TokenSet + frame.node.edges[charB] = transposeNode + } + + if (frame.str.length == 1) { + transposeNode.final = true + } + + stack.push({ + node: transposeNode, + editsRemaining: frame.editsRemaining - 1, + str: charA + frame.str.slice(2) + }) + } + } + + return root +} + +/** + * Creates a TokenSet from a string. + * + * The string may contain one or more wildcard characters (*) + * that will allow wildcard matching when intersecting with + * another TokenSet. + * + * @param {string} str - The string to create a TokenSet from. + * @returns {lunr.TokenSet} + */ +lunr.TokenSet.fromString = function (str) { + var node = new lunr.TokenSet, + root = node + + /* + * Iterates through all characters within the passed string + * appending a node for each character. + * + * When a wildcard character is found then a self + * referencing edge is introduced to continually match + * any number of any characters. + */ + for (var i = 0, len = str.length; i < len; i++) { + var char = str[i], + final = (i == len - 1) + + if (char == "*") { + node.edges[char] = node + node.final = final + + } else { + var next = new lunr.TokenSet + next.final = final + + node.edges[char] = next + node = next + } + } + + return root +} + +/** + * Converts this TokenSet into an array of strings + * contained within the TokenSet. + * + * This is not intended to be used on a TokenSet that + * contains wildcards, in these cases the results are + * undefined and are likely to cause an infinite loop. + * + * @returns {string[]} + */ +lunr.TokenSet.prototype.toArray = function () { + var words = [] + + var stack = [{ + prefix: "", + node: this + }] + + while (stack.length) { + var frame = stack.pop(), + edges = Object.keys(frame.node.edges), + len = edges.length + + if (frame.node.final) { + /* In Safari, at this point the prefix is sometimes corrupted, see: + * https://github.com/olivernn/lunr.js/issues/279 Calling any + * String.prototype method forces Safari to "cast" this string to what + * it's supposed to be, fixing the bug. */ + frame.prefix.charAt(0) + words.push(frame.prefix) + } + + for (var i = 0; i < len; i++) { + var edge = edges[i] + + stack.push({ + prefix: frame.prefix.concat(edge), + node: frame.node.edges[edge] + }) + } + } + + return words +} + +/** + * Generates a string representation of a TokenSet. + * + * This is intended to allow TokenSets to be used as keys + * in objects, largely to aid the construction and minimisation + * of a TokenSet. As such it is not designed to be a human + * friendly representation of the TokenSet. + * + * @returns {string} + */ +lunr.TokenSet.prototype.toString = function () { + // NOTE: Using Object.keys here as this.edges is very likely + // to enter 'hash-mode' with many keys being added + // + // avoiding a for-in loop here as it leads to the function + // being de-optimised (at least in V8). From some simple + // benchmarks the performance is comparable, but allowing + // V8 to optimize may mean easy performance wins in the future. + + if (this._str) { + return this._str + } + + var str = this.final ? '1' : '0', + labels = Object.keys(this.edges).sort(), + len = labels.length + + for (var i = 0; i < len; i++) { + var label = labels[i], + node = this.edges[label] + + str = str + label + node.id + } + + return str +} + +/** + * Returns a new TokenSet that is the intersection of + * this TokenSet and the passed TokenSet. + * + * This intersection will take into account any wildcards + * contained within the TokenSet. + * + * @param {lunr.TokenSet} b - An other TokenSet to intersect with. + * @returns {lunr.TokenSet} + */ +lunr.TokenSet.prototype.intersect = function (b) { + var output = new lunr.TokenSet, + frame = undefined + + var stack = [{ + qNode: b, + output: output, + node: this + }] + + while (stack.length) { + frame = stack.pop() + + // NOTE: As with the #toString method, we are using + // Object.keys and a for loop instead of a for-in loop + // as both of these objects enter 'hash' mode, causing + // the function to be de-optimised in V8 + var qEdges = Object.keys(frame.qNode.edges), + qLen = qEdges.length, + nEdges = Object.keys(frame.node.edges), + nLen = nEdges.length + + for (var q = 0; q < qLen; q++) { + var qEdge = qEdges[q] + + for (var n = 0; n < nLen; n++) { + var nEdge = nEdges[n] + + if (nEdge == qEdge || qEdge == '*') { + var node = frame.node.edges[nEdge], + qNode = frame.qNode.edges[qEdge], + final = node.final && qNode.final, + next = undefined + + if (nEdge in frame.output.edges) { + // an edge already exists for this character + // no need to create a new node, just set the finality + // bit unless this node is already final + next = frame.output.edges[nEdge] + next.final = next.final || final + + } else { + // no edge exists yet, must create one + // set the finality bit and insert it + // into the output + next = new lunr.TokenSet + next.final = final + frame.output.edges[nEdge] = next + } + + stack.push({ + qNode: qNode, + output: next, + node: node + }) + } + } + } + } + + return output +} +lunr.TokenSet.Builder = function () { + this.previousWord = "" + this.root = new lunr.TokenSet + this.uncheckedNodes = [] + this.minimizedNodes = {} +} + +lunr.TokenSet.Builder.prototype.insert = function (word) { + var node, + commonPrefix = 0 + + if (word < this.previousWord) { + throw new Error ("Out of order word insertion") + } + + for (var i = 0; i < word.length && i < this.previousWord.length; i++) { + if (word[i] != this.previousWord[i]) break + commonPrefix++ + } + + this.minimize(commonPrefix) + + if (this.uncheckedNodes.length == 0) { + node = this.root + } else { + node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child + } + + for (var i = commonPrefix; i < word.length; i++) { + var nextNode = new lunr.TokenSet, + char = word[i] + + node.edges[char] = nextNode + + this.uncheckedNodes.push({ + parent: node, + char: char, + child: nextNode + }) + + node = nextNode + } + + node.final = true + this.previousWord = word +} + +lunr.TokenSet.Builder.prototype.finish = function () { + this.minimize(0) +} + +lunr.TokenSet.Builder.prototype.minimize = function (downTo) { + for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) { + var node = this.uncheckedNodes[i], + childKey = node.child.toString() + + if (childKey in this.minimizedNodes) { + node.parent.edges[node.char] = this.minimizedNodes[childKey] + } else { + // Cache the key for this node since + // we know it can't change anymore + node.child._str = childKey + + this.minimizedNodes[childKey] = node.child + } + + this.uncheckedNodes.pop() + } +} +/*! + * lunr.Index + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * An index contains the built index of all documents and provides a query interface + * to the index. + * + * Usually instances of lunr.Index will not be created using this constructor, instead + * lunr.Builder should be used to construct new indexes, or lunr.Index.load should be + * used to load previously built and serialized indexes. + * + * @constructor + * @param {Object} attrs - The attributes of the built search index. + * @param {Object} attrs.invertedIndex - An index of term/field to document reference. + * @param {Object} attrs.fieldVectors - Field vectors + * @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens. + * @param {string[]} attrs.fields - The names of indexed document fields. + * @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms. + */ +lunr.Index = function (attrs) { + this.invertedIndex = attrs.invertedIndex + this.fieldVectors = attrs.fieldVectors + this.tokenSet = attrs.tokenSet + this.fields = attrs.fields + this.pipeline = attrs.pipeline +} + +/** + * A result contains details of a document matching a search query. + * @typedef {Object} lunr.Index~Result + * @property {string} ref - The reference of the document this result represents. + * @property {number} score - A number between 0 and 1 representing how similar this document is to the query. + * @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match. + */ + +/** + * Although lunr provides the ability to create queries using lunr.Query, it also provides a simple + * query language which itself is parsed into an instance of lunr.Query. + * + * For programmatically building queries it is advised to directly use lunr.Query, the query language + * is best used for human entered text rather than program generated text. + * + * At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported + * and will be combined with OR, e.g `hello world` will match documents that contain either 'hello' + * or 'world', though those that contain both will rank higher in the results. + * + * Wildcards can be included in terms to match one or more unspecified characters, these wildcards can + * be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding + * wildcards will increase the number of documents that will be found but can also have a negative + * impact on query performance, especially with wildcards at the beginning of a term. + * + * Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term + * hello in the title field will match this query. Using a field not present in the index will lead + * to an error being thrown. + * + * Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term + * boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported + * to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2. + * Avoid large values for edit distance to improve query performance. + * + * Each term also supports a presence modifier. By default a term's presence in document is optional, however + * this can be changed to either required or prohibited. For a term's presence to be required in a document the + * term should be prefixed with a '+', e.g. `+foo bar` is a search for documents that must contain 'foo' and + * optionally contain 'bar'. Conversely a leading '-' sets the terms presence to prohibited, i.e. it must not + * appear in a document, e.g. `-foo bar` is a search for documents that do not contain 'foo' but may contain 'bar'. + * + * To escape special characters the backslash character '\' can be used, this allows searches to include + * characters that would normally be considered modifiers, e.g. `foo\~2` will search for a term "foo~2" instead + * of attempting to apply a boost of 2 to the search term "foo". + * + * @typedef {string} lunr.Index~QueryString + * @example Simple single term query + * hello + * @example Multiple term query + * hello world + * @example term scoped to a field + * title:hello + * @example term with a boost of 10 + * hello^10 + * @example term with an edit distance of 2 + * hello~2 + * @example terms with presence modifiers + * -foo +bar baz + */ + +/** + * Performs a search against the index using lunr query syntax. + * + * Results will be returned sorted by their score, the most relevant results + * will be returned first. For details on how the score is calculated, please see + * the {@link https://lunrjs.com/guides/searching.html#scoring|guide}. + * + * For more programmatic querying use lunr.Index#query. + * + * @param {lunr.Index~QueryString} queryString - A string containing a lunr query. + * @throws {lunr.QueryParseError} If the passed query string cannot be parsed. + * @returns {lunr.Index~Result[]} + */ +lunr.Index.prototype.search = function (queryString) { + return this.query(function (query) { + var parser = new lunr.QueryParser(queryString, query) + parser.parse() + }) +} + +/** + * A query builder callback provides a query object to be used to express + * the query to perform on the index. + * + * @callback lunr.Index~queryBuilder + * @param {lunr.Query} query - The query object to build up. + * @this lunr.Query + */ + +/** + * Performs a query against the index using the yielded lunr.Query object. + * + * If performing programmatic queries against the index, this method is preferred + * over lunr.Index#search so as to avoid the additional query parsing overhead. + * + * A query object is yielded to the supplied function which should be used to + * express the query to be run against the index. + * + * Note that although this function takes a callback parameter it is _not_ an + * asynchronous operation, the callback is just yielded a query object to be + * customized. + * + * @param {lunr.Index~queryBuilder} fn - A function that is used to build the query. + * @returns {lunr.Index~Result[]} + */ +lunr.Index.prototype.query = function (fn) { + // for each query clause + // * process terms + // * expand terms from token set + // * find matching documents and metadata + // * get document vectors + // * score documents + + var query = new lunr.Query(this.fields), + matchingFields = Object.create(null), + queryVectors = Object.create(null), + termFieldCache = Object.create(null), + requiredMatches = Object.create(null), + prohibitedMatches = Object.create(null) + + /* + * To support field level boosts a query vector is created per + * field. An empty vector is eagerly created to support negated + * queries. + */ + for (var i = 0; i < this.fields.length; i++) { + queryVectors[this.fields[i]] = new lunr.Vector + } + + fn.call(query, query) + + for (var i = 0; i < query.clauses.length; i++) { + /* + * Unless the pipeline has been disabled for this term, which is + * the case for terms with wildcards, we need to pass the clause + * term through the search pipeline. A pipeline returns an array + * of processed terms. Pipeline functions may expand the passed + * term, which means we may end up performing multiple index lookups + * for a single query term. + */ + var clause = query.clauses[i], + terms = null, + clauseMatches = lunr.Set.empty + + if (clause.usePipeline) { + terms = this.pipeline.runString(clause.term, { + fields: clause.fields + }) + } else { + terms = [clause.term] + } + + for (var m = 0; m < terms.length; m++) { + var term = terms[m] + + /* + * Each term returned from the pipeline needs to use the same query + * clause object, e.g. the same boost and or edit distance. The + * simplest way to do this is to re-use the clause object but mutate + * its term property. + */ + clause.term = term + + /* + * From the term in the clause we create a token set which will then + * be used to intersect the indexes token set to get a list of terms + * to lookup in the inverted index + */ + var termTokenSet = lunr.TokenSet.fromClause(clause), + expandedTerms = this.tokenSet.intersect(termTokenSet).toArray() + + /* + * If a term marked as required does not exist in the tokenSet it is + * impossible for the search to return any matches. We set all the field + * scoped required matches set to empty and stop examining any further + * clauses. + */ + if (expandedTerms.length === 0 && clause.presence === lunr.Query.presence.REQUIRED) { + for (var k = 0; k < clause.fields.length; k++) { + var field = clause.fields[k] + requiredMatches[field] = lunr.Set.empty + } + + break + } + + for (var j = 0; j < expandedTerms.length; j++) { + /* + * For each term get the posting and termIndex, this is required for + * building the query vector. + */ + var expandedTerm = expandedTerms[j], + posting = this.invertedIndex[expandedTerm], + termIndex = posting._index + + for (var k = 0; k < clause.fields.length; k++) { + /* + * For each field that this query term is scoped by (by default + * all fields are in scope) we need to get all the document refs + * that have this term in that field. + * + * The posting is the entry in the invertedIndex for the matching + * term from above. + */ + var field = clause.fields[k], + fieldPosting = posting[field], + matchingDocumentRefs = Object.keys(fieldPosting), + termField = expandedTerm + "/" + field, + matchingDocumentsSet = new lunr.Set(matchingDocumentRefs) + + /* + * if the presence of this term is required ensure that the matching + * documents are added to the set of required matches for this clause. + * + */ + if (clause.presence == lunr.Query.presence.REQUIRED) { + clauseMatches = clauseMatches.union(matchingDocumentsSet) + + if (requiredMatches[field] === undefined) { + requiredMatches[field] = lunr.Set.complete + } + } + + /* + * if the presence of this term is prohibited ensure that the matching + * documents are added to the set of prohibited matches for this field, + * creating that set if it does not yet exist. + */ + if (clause.presence == lunr.Query.presence.PROHIBITED) { + if (prohibitedMatches[field] === undefined) { + prohibitedMatches[field] = lunr.Set.empty + } + + prohibitedMatches[field] = prohibitedMatches[field].union(matchingDocumentsSet) + + /* + * Prohibited matches should not be part of the query vector used for + * similarity scoring and no metadata should be extracted so we continue + * to the next field + */ + continue + } + + /* + * The query field vector is populated using the termIndex found for + * the term and a unit value with the appropriate boost applied. + * Using upsert because there could already be an entry in the vector + * for the term we are working with. In that case we just add the scores + * together. + */ + queryVectors[field].upsert(termIndex, clause.boost, function (a, b) { return a + b }) + + /** + * If we've already seen this term, field combo then we've already collected + * the matching documents and metadata, no need to go through all that again + */ + if (termFieldCache[termField]) { + continue + } + + for (var l = 0; l < matchingDocumentRefs.length; l++) { + /* + * All metadata for this term/field/document triple + * are then extracted and collected into an instance + * of lunr.MatchData ready to be returned in the query + * results + */ + var matchingDocumentRef = matchingDocumentRefs[l], + matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field), + metadata = fieldPosting[matchingDocumentRef], + fieldMatch + + if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) { + matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata) + } else { + fieldMatch.add(expandedTerm, field, metadata) + } + + } + + termFieldCache[termField] = true + } + } + } + + /** + * If the presence was required we need to update the requiredMatches field sets. + * We do this after all fields for the term have collected their matches because + * the clause terms presence is required in _any_ of the fields not _all_ of the + * fields. + */ + if (clause.presence === lunr.Query.presence.REQUIRED) { + for (var k = 0; k < clause.fields.length; k++) { + var field = clause.fields[k] + requiredMatches[field] = requiredMatches[field].intersect(clauseMatches) + } + } + } + + /** + * Need to combine the field scoped required and prohibited + * matching documents into a global set of required and prohibited + * matches + */ + var allRequiredMatches = lunr.Set.complete, + allProhibitedMatches = lunr.Set.empty + + for (var i = 0; i < this.fields.length; i++) { + var field = this.fields[i] + + if (requiredMatches[field]) { + allRequiredMatches = allRequiredMatches.intersect(requiredMatches[field]) + } + + if (prohibitedMatches[field]) { + allProhibitedMatches = allProhibitedMatches.union(prohibitedMatches[field]) + } + } + + var matchingFieldRefs = Object.keys(matchingFields), + results = [], + matches = Object.create(null) + + /* + * If the query is negated (contains only prohibited terms) + * we need to get _all_ fieldRefs currently existing in the + * index. This is only done when we know that the query is + * entirely prohibited terms to avoid any cost of getting all + * fieldRefs unnecessarily. + * + * Additionally, blank MatchData must be created to correctly + * populate the results. + */ + if (query.isNegated()) { + matchingFieldRefs = Object.keys(this.fieldVectors) + + for (var i = 0; i < matchingFieldRefs.length; i++) { + var matchingFieldRef = matchingFieldRefs[i] + var fieldRef = lunr.FieldRef.fromString(matchingFieldRef) + matchingFields[matchingFieldRef] = new lunr.MatchData + } + } + + for (var i = 0; i < matchingFieldRefs.length; i++) { + /* + * Currently we have document fields that match the query, but we + * need to return documents. The matchData and scores are combined + * from multiple fields belonging to the same document. + * + * Scores are calculated by field, using the query vectors created + * above, and combined into a final document score using addition. + */ + var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]), + docRef = fieldRef.docRef + + if (!allRequiredMatches.contains(docRef)) { + continue + } + + if (allProhibitedMatches.contains(docRef)) { + continue + } + + var fieldVector = this.fieldVectors[fieldRef], + score = queryVectors[fieldRef.fieldName].similarity(fieldVector), + docMatch + + if ((docMatch = matches[docRef]) !== undefined) { + docMatch.score += score + docMatch.matchData.combine(matchingFields[fieldRef]) + } else { + var match = { + ref: docRef, + score: score, + matchData: matchingFields[fieldRef] + } + matches[docRef] = match + results.push(match) + } + } + + /* + * Sort the results objects by score, highest first. + */ + return results.sort(function (a, b) { + return b.score - a.score + }) +} + +/** + * Prepares the index for JSON serialization. + * + * The schema for this JSON blob will be described in a + * separate JSON schema file. + * + * @returns {Object} + */ +lunr.Index.prototype.toJSON = function () { + var invertedIndex = Object.keys(this.invertedIndex) + .sort() + .map(function (term) { + return [term, this.invertedIndex[term]] + }, this) + + var fieldVectors = Object.keys(this.fieldVectors) + .map(function (ref) { + return [ref, this.fieldVectors[ref].toJSON()] + }, this) + + return { + version: lunr.version, + fields: this.fields, + fieldVectors: fieldVectors, + invertedIndex: invertedIndex, + pipeline: this.pipeline.toJSON() + } +} + +/** + * Loads a previously serialized lunr.Index + * + * @param {Object} serializedIndex - A previously serialized lunr.Index + * @returns {lunr.Index} + */ +lunr.Index.load = function (serializedIndex) { + var attrs = {}, + fieldVectors = {}, + serializedVectors = serializedIndex.fieldVectors, + invertedIndex = Object.create(null), + serializedInvertedIndex = serializedIndex.invertedIndex, + tokenSetBuilder = new lunr.TokenSet.Builder, + pipeline = lunr.Pipeline.load(serializedIndex.pipeline) + + if (serializedIndex.version != lunr.version) { + lunr.utils.warn("Version mismatch when loading serialised index. Current version of lunr '" + lunr.version + "' does not match serialized index '" + serializedIndex.version + "'") + } + + for (var i = 0; i < serializedVectors.length; i++) { + var tuple = serializedVectors[i], + ref = tuple[0], + elements = tuple[1] + + fieldVectors[ref] = new lunr.Vector(elements) + } + + for (var i = 0; i < serializedInvertedIndex.length; i++) { + var tuple = serializedInvertedIndex[i], + term = tuple[0], + posting = tuple[1] + + tokenSetBuilder.insert(term) + invertedIndex[term] = posting + } + + tokenSetBuilder.finish() + + attrs.fields = serializedIndex.fields + + attrs.fieldVectors = fieldVectors + attrs.invertedIndex = invertedIndex + attrs.tokenSet = tokenSetBuilder.root + attrs.pipeline = pipeline + + return new lunr.Index(attrs) +} +/*! + * lunr.Builder + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.Builder performs indexing on a set of documents and + * returns instances of lunr.Index ready for querying. + * + * All configuration of the index is done via the builder, the + * fields to index, the document reference, the text processing + * pipeline and document scoring parameters are all set on the + * builder before indexing. + * + * @constructor + * @property {string} _ref - Internal reference to the document reference field. + * @property {string[]} _fields - Internal reference to the document fields to index. + * @property {object} invertedIndex - The inverted index maps terms to document fields. + * @property {object} documentTermFrequencies - Keeps track of document term frequencies. + * @property {object} documentLengths - Keeps track of the length of documents added to the index. + * @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing. + * @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing. + * @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index. + * @property {number} documentCount - Keeps track of the total number of documents indexed. + * @property {number} _b - A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75. + * @property {number} _k1 - A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2. + * @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space. + * @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index. + */ +lunr.Builder = function () { + this._ref = "id" + this._fields = Object.create(null) + this._documents = Object.create(null) + this.invertedIndex = Object.create(null) + this.fieldTermFrequencies = {} + this.fieldLengths = {} + this.tokenizer = lunr.tokenizer + this.pipeline = new lunr.Pipeline + this.searchPipeline = new lunr.Pipeline + this.documentCount = 0 + this._b = 0.75 + this._k1 = 1.2 + this.termIndex = 0 + this.metadataWhitelist = [] +} + +/** + * Sets the document field used as the document reference. Every document must have this field. + * The type of this field in the document should be a string, if it is not a string it will be + * coerced into a string by calling toString. + * + * The default ref is 'id'. + * + * The ref should _not_ be changed during indexing, it should be set before any documents are + * added to the index. Changing it during indexing can lead to inconsistent results. + * + * @param {string} ref - The name of the reference field in the document. + */ +lunr.Builder.prototype.ref = function (ref) { + this._ref = ref +} + +/** + * A function that is used to extract a field from a document. + * + * Lunr expects a field to be at the top level of a document, if however the field + * is deeply nested within a document an extractor function can be used to extract + * the right field for indexing. + * + * @callback fieldExtractor + * @param {object} doc - The document being added to the index. + * @returns {?(string|object|object[])} obj - The object that will be indexed for this field. + * @example Extracting a nested field + * function (doc) { return doc.nested.field } + */ + +/** + * Adds a field to the list of document fields that will be indexed. Every document being + * indexed should have this field. Null values for this field in indexed documents will + * not cause errors but will limit the chance of that document being retrieved by searches. + * + * All fields should be added before adding documents to the index. Adding fields after + * a document has been indexed will have no effect on already indexed documents. + * + * Fields can be boosted at build time. This allows terms within that field to have more + * importance when ranking search results. Use a field boost to specify that matches within + * one field are more important than other fields. + * + * @param {string} fieldName - The name of a field to index in all documents. + * @param {object} attributes - Optional attributes associated with this field. + * @param {number} [attributes.boost=1] - Boost applied to all terms within this field. + * @param {fieldExtractor} [attributes.extractor] - Function to extract a field from a document. + * @throws {RangeError} fieldName cannot contain unsupported characters '/' + */ +lunr.Builder.prototype.field = function (fieldName, attributes) { + if (/\//.test(fieldName)) { + throw new RangeError ("Field '" + fieldName + "' contains illegal character '/'") + } + + this._fields[fieldName] = attributes || {} +} + +/** + * A parameter to tune the amount of field length normalisation that is applied when + * calculating relevance scores. A value of 0 will completely disable any normalisation + * and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b + * will be clamped to the range 0 - 1. + * + * @param {number} number - The value to set for this tuning parameter. + */ +lunr.Builder.prototype.b = function (number) { + if (number < 0) { + this._b = 0 + } else if (number > 1) { + this._b = 1 + } else { + this._b = number + } +} + +/** + * A parameter that controls the speed at which a rise in term frequency results in term + * frequency saturation. The default value is 1.2. Setting this to a higher value will give + * slower saturation levels, a lower value will result in quicker saturation. + * + * @param {number} number - The value to set for this tuning parameter. + */ +lunr.Builder.prototype.k1 = function (number) { + this._k1 = number +} + +/** + * Adds a document to the index. + * + * Before adding fields to the index the index should have been fully setup, with the document + * ref and all fields to index already having been specified. + * + * The document must have a field name as specified by the ref (by default this is 'id') and + * it should have all fields defined for indexing, though null or undefined values will not + * cause errors. + * + * Entire documents can be boosted at build time. Applying a boost to a document indicates that + * this document should rank higher in search results than other documents. + * + * @param {object} doc - The document to add to the index. + * @param {object} attributes - Optional attributes associated with this document. + * @param {number} [attributes.boost=1] - Boost applied to all terms within this document. + */ +lunr.Builder.prototype.add = function (doc, attributes) { + var docRef = doc[this._ref], + fields = Object.keys(this._fields) + + this._documents[docRef] = attributes || {} + this.documentCount += 1 + + for (var i = 0; i < fields.length; i++) { + var fieldName = fields[i], + extractor = this._fields[fieldName].extractor, + field = extractor ? extractor(doc) : doc[fieldName], + tokens = this.tokenizer(field, { + fields: [fieldName] + }), + terms = this.pipeline.run(tokens), + fieldRef = new lunr.FieldRef (docRef, fieldName), + fieldTerms = Object.create(null) + + this.fieldTermFrequencies[fieldRef] = fieldTerms + this.fieldLengths[fieldRef] = 0 + + // store the length of this field for this document + this.fieldLengths[fieldRef] += terms.length + + // calculate term frequencies for this field + for (var j = 0; j < terms.length; j++) { + var term = terms[j] + + if (fieldTerms[term] == undefined) { + fieldTerms[term] = 0 + } + + fieldTerms[term] += 1 + + // add to inverted index + // create an initial posting if one doesn't exist + if (this.invertedIndex[term] == undefined) { + var posting = Object.create(null) + posting["_index"] = this.termIndex + this.termIndex += 1 + + for (var k = 0; k < fields.length; k++) { + posting[fields[k]] = Object.create(null) + } + + this.invertedIndex[term] = posting + } + + // add an entry for this term/fieldName/docRef to the invertedIndex + if (this.invertedIndex[term][fieldName][docRef] == undefined) { + this.invertedIndex[term][fieldName][docRef] = Object.create(null) + } + + // store all whitelisted metadata about this token in the + // inverted index + for (var l = 0; l < this.metadataWhitelist.length; l++) { + var metadataKey = this.metadataWhitelist[l], + metadata = term.metadata[metadataKey] + + if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) { + this.invertedIndex[term][fieldName][docRef][metadataKey] = [] + } + + this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata) + } + } + + } +} + +/** + * Calculates the average document length for this index + * + * @private + */ +lunr.Builder.prototype.calculateAverageFieldLengths = function () { + + var fieldRefs = Object.keys(this.fieldLengths), + numberOfFields = fieldRefs.length, + accumulator = {}, + documentsWithField = {} + + for (var i = 0; i < numberOfFields; i++) { + var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]), + field = fieldRef.fieldName + + documentsWithField[field] || (documentsWithField[field] = 0) + documentsWithField[field] += 1 + + accumulator[field] || (accumulator[field] = 0) + accumulator[field] += this.fieldLengths[fieldRef] + } + + var fields = Object.keys(this._fields) + + for (var i = 0; i < fields.length; i++) { + var fieldName = fields[i] + accumulator[fieldName] = accumulator[fieldName] / documentsWithField[fieldName] + } + + this.averageFieldLength = accumulator +} + +/** + * Builds a vector space model of every document using lunr.Vector + * + * @private + */ +lunr.Builder.prototype.createFieldVectors = function () { + var fieldVectors = {}, + fieldRefs = Object.keys(this.fieldTermFrequencies), + fieldRefsLength = fieldRefs.length, + termIdfCache = Object.create(null) + + for (var i = 0; i < fieldRefsLength; i++) { + var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]), + fieldName = fieldRef.fieldName, + fieldLength = this.fieldLengths[fieldRef], + fieldVector = new lunr.Vector, + termFrequencies = this.fieldTermFrequencies[fieldRef], + terms = Object.keys(termFrequencies), + termsLength = terms.length + + + var fieldBoost = this._fields[fieldName].boost || 1, + docBoost = this._documents[fieldRef.docRef].boost || 1 + + for (var j = 0; j < termsLength; j++) { + var term = terms[j], + tf = termFrequencies[term], + termIndex = this.invertedIndex[term]._index, + idf, score, scoreWithPrecision + + if (termIdfCache[term] === undefined) { + idf = lunr.idf(this.invertedIndex[term], this.documentCount) + termIdfCache[term] = idf + } else { + idf = termIdfCache[term] + } + + score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[fieldName])) + tf) + score *= fieldBoost + score *= docBoost + scoreWithPrecision = Math.round(score * 1000) / 1000 + // Converts 1.23456789 to 1.234. + // Reducing the precision so that the vectors take up less + // space when serialised. Doing it now so that they behave + // the same before and after serialisation. Also, this is + // the fastest approach to reducing a number's precision in + // JavaScript. + + fieldVector.insert(termIndex, scoreWithPrecision) + } + + fieldVectors[fieldRef] = fieldVector + } + + this.fieldVectors = fieldVectors +} + +/** + * Creates a token set of all tokens in the index using lunr.TokenSet + * + * @private + */ +lunr.Builder.prototype.createTokenSet = function () { + this.tokenSet = lunr.TokenSet.fromArray( + Object.keys(this.invertedIndex).sort() + ) +} + +/** + * Builds the index, creating an instance of lunr.Index. + * + * This completes the indexing process and should only be called + * once all documents have been added to the index. + * + * @returns {lunr.Index} + */ +lunr.Builder.prototype.build = function () { + this.calculateAverageFieldLengths() + this.createFieldVectors() + this.createTokenSet() + + return new lunr.Index({ + invertedIndex: this.invertedIndex, + fieldVectors: this.fieldVectors, + tokenSet: this.tokenSet, + fields: Object.keys(this._fields), + pipeline: this.searchPipeline + }) +} + +/** + * Applies a plugin to the index builder. + * + * A plugin is a function that is called with the index builder as its context. + * Plugins can be used to customise or extend the behaviour of the index + * in some way. A plugin is just a function, that encapsulated the custom + * behaviour that should be applied when building the index. + * + * The plugin function will be called with the index builder as its argument, additional + * arguments can also be passed when calling use. The function will be called + * with the index builder as its context. + * + * @param {Function} plugin The plugin to apply. + */ +lunr.Builder.prototype.use = function (fn) { + var args = Array.prototype.slice.call(arguments, 1) + args.unshift(this) + fn.apply(this, args) +} +/** + * Contains and collects metadata about a matching document. + * A single instance of lunr.MatchData is returned as part of every + * lunr.Index~Result. + * + * @constructor + * @param {string} term - The term this match data is associated with + * @param {string} field - The field in which the term was found + * @param {object} metadata - The metadata recorded about this term in this field + * @property {object} metadata - A cloned collection of metadata associated with this document. + * @see {@link lunr.Index~Result} + */ +lunr.MatchData = function (term, field, metadata) { + var clonedMetadata = Object.create(null), + metadataKeys = Object.keys(metadata || {}) + + // Cloning the metadata to prevent the original + // being mutated during match data combination. + // Metadata is kept in an array within the inverted + // index so cloning the data can be done with + // Array#slice + for (var i = 0; i < metadataKeys.length; i++) { + var key = metadataKeys[i] + clonedMetadata[key] = metadata[key].slice() + } + + this.metadata = Object.create(null) + + if (term !== undefined) { + this.metadata[term] = Object.create(null) + this.metadata[term][field] = clonedMetadata + } +} + +/** + * An instance of lunr.MatchData will be created for every term that matches a + * document. However only one instance is required in a lunr.Index~Result. This + * method combines metadata from another instance of lunr.MatchData with this + * objects metadata. + * + * @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one. + * @see {@link lunr.Index~Result} + */ +lunr.MatchData.prototype.combine = function (otherMatchData) { + var terms = Object.keys(otherMatchData.metadata) + + for (var i = 0; i < terms.length; i++) { + var term = terms[i], + fields = Object.keys(otherMatchData.metadata[term]) + + if (this.metadata[term] == undefined) { + this.metadata[term] = Object.create(null) + } + + for (var j = 0; j < fields.length; j++) { + var field = fields[j], + keys = Object.keys(otherMatchData.metadata[term][field]) + + if (this.metadata[term][field] == undefined) { + this.metadata[term][field] = Object.create(null) + } + + for (var k = 0; k < keys.length; k++) { + var key = keys[k] + + if (this.metadata[term][field][key] == undefined) { + this.metadata[term][field][key] = otherMatchData.metadata[term][field][key] + } else { + this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key]) + } + + } + } + } +} + +/** + * Add metadata for a term/field pair to this instance of match data. + * + * @param {string} term - The term this match data is associated with + * @param {string} field - The field in which the term was found + * @param {object} metadata - The metadata recorded about this term in this field + */ +lunr.MatchData.prototype.add = function (term, field, metadata) { + if (!(term in this.metadata)) { + this.metadata[term] = Object.create(null) + this.metadata[term][field] = metadata + return + } + + if (!(field in this.metadata[term])) { + this.metadata[term][field] = metadata + return + } + + var metadataKeys = Object.keys(metadata) + + for (var i = 0; i < metadataKeys.length; i++) { + var key = metadataKeys[i] + + if (key in this.metadata[term][field]) { + this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key]) + } else { + this.metadata[term][field][key] = metadata[key] + } + } +} +/** + * A lunr.Query provides a programmatic way of defining queries to be performed + * against a {@link lunr.Index}. + * + * Prefer constructing a lunr.Query using the {@link lunr.Index#query} method + * so the query object is pre-initialized with the right index fields. + * + * @constructor + * @property {lunr.Query~Clause[]} clauses - An array of query clauses. + * @property {string[]} allFields - An array of all available fields in a lunr.Index. + */ +lunr.Query = function (allFields) { + this.clauses = [] + this.allFields = allFields +} + +/** + * Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause. + * + * This allows wildcards to be added to the beginning and end of a term without having to manually do any string + * concatenation. + * + * The wildcard constants can be bitwise combined to select both leading and trailing wildcards. + * + * @constant + * @default + * @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour + * @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists + * @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists + * @see lunr.Query~Clause + * @see lunr.Query#clause + * @see lunr.Query#term + * @example query term with trailing wildcard + * query.term('foo', { wildcard: lunr.Query.wildcard.TRAILING }) + * @example query term with leading and trailing wildcard + * query.term('foo', { + * wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING + * }) + */ + +lunr.Query.wildcard = new String ("*") +lunr.Query.wildcard.NONE = 0 +lunr.Query.wildcard.LEADING = 1 +lunr.Query.wildcard.TRAILING = 2 + +/** + * Constants for indicating what kind of presence a term must have in matching documents. + * + * @constant + * @enum {number} + * @see lunr.Query~Clause + * @see lunr.Query#clause + * @see lunr.Query#term + * @example query term with required presence + * query.term('foo', { presence: lunr.Query.presence.REQUIRED }) + */ +lunr.Query.presence = { + /** + * Term's presence in a document is optional, this is the default value. + */ + OPTIONAL: 1, + + /** + * Term's presence in a document is required, documents that do not contain + * this term will not be returned. + */ + REQUIRED: 2, + + /** + * Term's presence in a document is prohibited, documents that do contain + * this term will not be returned. + */ + PROHIBITED: 3 +} + +/** + * A single clause in a {@link lunr.Query} contains a term and details on how to + * match that term against a {@link lunr.Index}. + * + * @typedef {Object} lunr.Query~Clause + * @property {string[]} fields - The fields in an index this clause should be matched against. + * @property {number} [boost=1] - Any boost that should be applied when matching this clause. + * @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be. + * @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline. + * @property {number} [wildcard=lunr.Query.wildcard.NONE] - Whether the term should have wildcards appended or prepended. + * @property {number} [presence=lunr.Query.presence.OPTIONAL] - The terms presence in any matching documents. + */ + +/** + * Adds a {@link lunr.Query~Clause} to this query. + * + * Unless the clause contains the fields to be matched all fields will be matched. In addition + * a default boost of 1 is applied to the clause. + * + * @param {lunr.Query~Clause} clause - The clause to add to this query. + * @see lunr.Query~Clause + * @returns {lunr.Query} + */ +lunr.Query.prototype.clause = function (clause) { + if (!('fields' in clause)) { + clause.fields = this.allFields + } + + if (!('boost' in clause)) { + clause.boost = 1 + } + + if (!('usePipeline' in clause)) { + clause.usePipeline = true + } + + if (!('wildcard' in clause)) { + clause.wildcard = lunr.Query.wildcard.NONE + } + + if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) { + clause.term = "*" + clause.term + } + + if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) { + clause.term = "" + clause.term + "*" + } + + if (!('presence' in clause)) { + clause.presence = lunr.Query.presence.OPTIONAL + } + + this.clauses.push(clause) + + return this +} + +/** + * A negated query is one in which every clause has a presence of + * prohibited. These queries require some special processing to return + * the expected results. + * + * @returns boolean + */ +lunr.Query.prototype.isNegated = function () { + for (var i = 0; i < this.clauses.length; i++) { + if (this.clauses[i].presence != lunr.Query.presence.PROHIBITED) { + return false + } + } + + return true +} + +/** + * Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause} + * to the list of clauses that make up this query. + * + * The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion + * to a token or token-like string should be done before calling this method. + * + * The term will be converted to a string by calling `toString`. Multiple terms can be passed as an + * array, each term in the array will share the same options. + * + * @param {object|object[]} term - The term(s) to add to the query. + * @param {object} [options] - Any additional properties to add to the query clause. + * @returns {lunr.Query} + * @see lunr.Query#clause + * @see lunr.Query~Clause + * @example adding a single term to a query + * query.term("foo") + * @example adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard + * query.term("foo", { + * fields: ["title"], + * boost: 10, + * wildcard: lunr.Query.wildcard.TRAILING + * }) + * @example using lunr.tokenizer to convert a string to tokens before using them as terms + * query.term(lunr.tokenizer("foo bar")) + */ +lunr.Query.prototype.term = function (term, options) { + if (Array.isArray(term)) { + term.forEach(function (t) { this.term(t, lunr.utils.clone(options)) }, this) + return this + } + + var clause = options || {} + clause.term = term.toString() + + this.clause(clause) + + return this +} +lunr.QueryParseError = function (message, start, end) { + this.name = "QueryParseError" + this.message = message + this.start = start + this.end = end +} + +lunr.QueryParseError.prototype = new Error +lunr.QueryLexer = function (str) { + this.lexemes = [] + this.str = str + this.length = str.length + this.pos = 0 + this.start = 0 + this.escapeCharPositions = [] +} + +lunr.QueryLexer.prototype.run = function () { + var state = lunr.QueryLexer.lexText + + while (state) { + state = state(this) + } +} + +lunr.QueryLexer.prototype.sliceString = function () { + var subSlices = [], + sliceStart = this.start, + sliceEnd = this.pos + + for (var i = 0; i < this.escapeCharPositions.length; i++) { + sliceEnd = this.escapeCharPositions[i] + subSlices.push(this.str.slice(sliceStart, sliceEnd)) + sliceStart = sliceEnd + 1 + } + + subSlices.push(this.str.slice(sliceStart, this.pos)) + this.escapeCharPositions.length = 0 + + return subSlices.join('') +} + +lunr.QueryLexer.prototype.emit = function (type) { + this.lexemes.push({ + type: type, + str: this.sliceString(), + start: this.start, + end: this.pos + }) + + this.start = this.pos +} + +lunr.QueryLexer.prototype.escapeCharacter = function () { + this.escapeCharPositions.push(this.pos - 1) + this.pos += 1 +} + +lunr.QueryLexer.prototype.next = function () { + if (this.pos >= this.length) { + return lunr.QueryLexer.EOS + } + + var char = this.str.charAt(this.pos) + this.pos += 1 + return char +} + +lunr.QueryLexer.prototype.width = function () { + return this.pos - this.start +} + +lunr.QueryLexer.prototype.ignore = function () { + if (this.start == this.pos) { + this.pos += 1 + } + + this.start = this.pos +} + +lunr.QueryLexer.prototype.backup = function () { + this.pos -= 1 +} + +lunr.QueryLexer.prototype.acceptDigitRun = function () { + var char, charCode + + do { + char = this.next() + charCode = char.charCodeAt(0) + } while (charCode > 47 && charCode < 58) + + if (char != lunr.QueryLexer.EOS) { + this.backup() + } +} + +lunr.QueryLexer.prototype.more = function () { + return this.pos < this.length +} + +lunr.QueryLexer.EOS = 'EOS' +lunr.QueryLexer.FIELD = 'FIELD' +lunr.QueryLexer.TERM = 'TERM' +lunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE' +lunr.QueryLexer.BOOST = 'BOOST' +lunr.QueryLexer.PRESENCE = 'PRESENCE' + +lunr.QueryLexer.lexField = function (lexer) { + lexer.backup() + lexer.emit(lunr.QueryLexer.FIELD) + lexer.ignore() + return lunr.QueryLexer.lexText +} + +lunr.QueryLexer.lexTerm = function (lexer) { + if (lexer.width() > 1) { + lexer.backup() + lexer.emit(lunr.QueryLexer.TERM) + } + + lexer.ignore() + + if (lexer.more()) { + return lunr.QueryLexer.lexText + } +} + +lunr.QueryLexer.lexEditDistance = function (lexer) { + lexer.ignore() + lexer.acceptDigitRun() + lexer.emit(lunr.QueryLexer.EDIT_DISTANCE) + return lunr.QueryLexer.lexText +} + +lunr.QueryLexer.lexBoost = function (lexer) { + lexer.ignore() + lexer.acceptDigitRun() + lexer.emit(lunr.QueryLexer.BOOST) + return lunr.QueryLexer.lexText +} + +lunr.QueryLexer.lexEOS = function (lexer) { + if (lexer.width() > 0) { + lexer.emit(lunr.QueryLexer.TERM) + } +} + +// This matches the separator used when tokenising fields +// within a document. These should match otherwise it is +// not possible to search for some tokens within a document. +// +// It is possible for the user to change the separator on the +// tokenizer so it _might_ clash with any other of the special +// characters already used within the search string, e.g. :. +// +// This means that it is possible to change the separator in +// such a way that makes some words unsearchable using a search +// string. +lunr.QueryLexer.termSeparator = lunr.tokenizer.separator + +lunr.QueryLexer.lexText = function (lexer) { + while (true) { + var char = lexer.next() + + if (char == lunr.QueryLexer.EOS) { + return lunr.QueryLexer.lexEOS + } + + // Escape character is '\' + if (char.charCodeAt(0) == 92) { + lexer.escapeCharacter() + continue + } + + if (char == ":") { + return lunr.QueryLexer.lexField + } + + if (char == "~") { + lexer.backup() + if (lexer.width() > 0) { + lexer.emit(lunr.QueryLexer.TERM) + } + return lunr.QueryLexer.lexEditDistance + } + + if (char == "^") { + lexer.backup() + if (lexer.width() > 0) { + lexer.emit(lunr.QueryLexer.TERM) + } + return lunr.QueryLexer.lexBoost + } + + // "+" indicates term presence is required + // checking for length to ensure that only + // leading "+" are considered + if (char == "+" && lexer.width() === 1) { + lexer.emit(lunr.QueryLexer.PRESENCE) + return lunr.QueryLexer.lexText + } + + // "-" indicates term presence is prohibited + // checking for length to ensure that only + // leading "-" are considered + if (char == "-" && lexer.width() === 1) { + lexer.emit(lunr.QueryLexer.PRESENCE) + return lunr.QueryLexer.lexText + } + + if (char.match(lunr.QueryLexer.termSeparator)) { + return lunr.QueryLexer.lexTerm + } + } +} + +lunr.QueryParser = function (str, query) { + this.lexer = new lunr.QueryLexer (str) + this.query = query + this.currentClause = {} + this.lexemeIdx = 0 +} + +lunr.QueryParser.prototype.parse = function () { + this.lexer.run() + this.lexemes = this.lexer.lexemes + + var state = lunr.QueryParser.parseClause + + while (state) { + state = state(this) + } + + return this.query +} + +lunr.QueryParser.prototype.peekLexeme = function () { + return this.lexemes[this.lexemeIdx] +} + +lunr.QueryParser.prototype.consumeLexeme = function () { + var lexeme = this.peekLexeme() + this.lexemeIdx += 1 + return lexeme +} + +lunr.QueryParser.prototype.nextClause = function () { + var completedClause = this.currentClause + this.query.clause(completedClause) + this.currentClause = {} +} + +lunr.QueryParser.parseClause = function (parser) { + var lexeme = parser.peekLexeme() + + if (lexeme == undefined) { + return + } + + switch (lexeme.type) { + case lunr.QueryLexer.PRESENCE: + return lunr.QueryParser.parsePresence + case lunr.QueryLexer.FIELD: + return lunr.QueryParser.parseField + case lunr.QueryLexer.TERM: + return lunr.QueryParser.parseTerm + default: + var errorMessage = "expected either a field or a term, found " + lexeme.type + + if (lexeme.str.length >= 1) { + errorMessage += " with value '" + lexeme.str + "'" + } + + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } +} + +lunr.QueryParser.parsePresence = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + switch (lexeme.str) { + case "-": + parser.currentClause.presence = lunr.Query.presence.PROHIBITED + break + case "+": + parser.currentClause.presence = lunr.Query.presence.REQUIRED + break + default: + var errorMessage = "unrecognised presence operator'" + lexeme.str + "'" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + var errorMessage = "expecting term or field, found nothing" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.FIELD: + return lunr.QueryParser.parseField + case lunr.QueryLexer.TERM: + return lunr.QueryParser.parseTerm + default: + var errorMessage = "expecting term or field, found '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseField = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + if (parser.query.allFields.indexOf(lexeme.str) == -1) { + var possibleFields = parser.query.allFields.map(function (f) { return "'" + f + "'" }).join(', '), + errorMessage = "unrecognised field '" + lexeme.str + "', possible fields: " + possibleFields + + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + parser.currentClause.fields = [lexeme.str] + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + var errorMessage = "expecting term, found nothing" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + return lunr.QueryParser.parseTerm + default: + var errorMessage = "expecting term, found '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseTerm = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + parser.currentClause.term = lexeme.str.toLowerCase() + + if (lexeme.str.indexOf("*") != -1) { + parser.currentClause.usePipeline = false + } + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + parser.nextClause() + return + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + parser.nextClause() + return lunr.QueryParser.parseTerm + case lunr.QueryLexer.FIELD: + parser.nextClause() + return lunr.QueryParser.parseField + case lunr.QueryLexer.EDIT_DISTANCE: + return lunr.QueryParser.parseEditDistance + case lunr.QueryLexer.BOOST: + return lunr.QueryParser.parseBoost + case lunr.QueryLexer.PRESENCE: + parser.nextClause() + return lunr.QueryParser.parsePresence + default: + var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseEditDistance = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + var editDistance = parseInt(lexeme.str, 10) + + if (isNaN(editDistance)) { + var errorMessage = "edit distance must be numeric" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + parser.currentClause.editDistance = editDistance + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + parser.nextClause() + return + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + parser.nextClause() + return lunr.QueryParser.parseTerm + case lunr.QueryLexer.FIELD: + parser.nextClause() + return lunr.QueryParser.parseField + case lunr.QueryLexer.EDIT_DISTANCE: + return lunr.QueryParser.parseEditDistance + case lunr.QueryLexer.BOOST: + return lunr.QueryParser.parseBoost + case lunr.QueryLexer.PRESENCE: + parser.nextClause() + return lunr.QueryParser.parsePresence + default: + var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseBoost = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + var boost = parseInt(lexeme.str, 10) + + if (isNaN(boost)) { + var errorMessage = "boost must be numeric" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + parser.currentClause.boost = boost + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + parser.nextClause() + return + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + parser.nextClause() + return lunr.QueryParser.parseTerm + case lunr.QueryLexer.FIELD: + parser.nextClause() + return lunr.QueryParser.parseField + case lunr.QueryLexer.EDIT_DISTANCE: + return lunr.QueryParser.parseEditDistance + case lunr.QueryLexer.BOOST: + return lunr.QueryParser.parseBoost + case lunr.QueryLexer.PRESENCE: + parser.nextClause() + return lunr.QueryParser.parsePresence + default: + var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + + /** + * export the module via AMD, CommonJS or as a browser global + * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js + */ + ;(function (root, factory) { + if (typeof define === 'function' && define.amd) { + // AMD. Register as an anonymous module. + define(factory) + } else if (typeof exports === 'object') { + /** + * Node. Does not work with strict CommonJS, but + * only CommonJS-like environments that support module.exports, + * like Node. + */ + module.exports = factory() + } else { + // Browser globals (root is window) + root.lunr = factory() + } + }(this, function () { + /** + * Just return a value to define the module export. + * This example returns an object, but the module + * can return a function as the exported value. + */ + return lunr + })) +})(); diff --git a/search/main.js b/search/main.js new file mode 100644 index 000000000..a5e469d7c --- /dev/null +++ b/search/main.js @@ -0,0 +1,109 @@ +function getSearchTermFromLocation() { + var sPageURL = window.location.search.substring(1); + var sURLVariables = sPageURL.split('&'); + for (var i = 0; i < sURLVariables.length; i++) { + var sParameterName = sURLVariables[i].split('='); + if (sParameterName[0] == 'q') { + return decodeURIComponent(sParameterName[1].replace(/\+/g, '%20')); + } + } +} + +function joinUrl (base, path) { + if (path.substring(0, 1) === "/") { + // path starts with `/`. Thus it is absolute. + return path; + } + if (base.substring(base.length-1) === "/") { + // base ends with `/` + return base + path; + } + return base + "/" + path; +} + +function escapeHtml (value) { + return value.replace(/&/g, '&') + .replace(/"/g, '"') + .replace(//g, '>'); +} + +function formatResult (location, title, summary) { + return ''; +} + +function displayResults (results) { + var search_results = document.getElementById("mkdocs-search-results"); + while (search_results.firstChild) { + search_results.removeChild(search_results.firstChild); + } + if (results.length > 0){ + for (var i=0; i < results.length; i++){ + var result = results[i]; + var html = formatResult(result.location, result.title, result.summary); + search_results.insertAdjacentHTML('beforeend', html); + } + } else { + var noResultsText = search_results.getAttribute('data-no-results-text'); + if (!noResultsText) { + noResultsText = "No results found"; + } + search_results.insertAdjacentHTML('beforeend', '

' + noResultsText + '

'); + } +} + +function doSearch () { + var query = document.getElementById('mkdocs-search-query').value; + if (query.length > min_search_length) { + if (!window.Worker) { + displayResults(search(query)); + } else { + searchWorker.postMessage({query: query}); + } + } else { + // Clear results for short queries + displayResults([]); + } +} + +function initSearch () { + var search_input = document.getElementById('mkdocs-search-query'); + if (search_input) { + search_input.addEventListener("keyup", doSearch); + } + var term = getSearchTermFromLocation(); + if (term) { + search_input.value = term; + doSearch(); + } +} + +function onWorkerMessage (e) { + if (e.data.allowSearch) { + initSearch(); + } else if (e.data.results) { + var results = e.data.results; + displayResults(results); + } else if (e.data.config) { + min_search_length = e.data.config.min_search_length-1; + } +} + +if (!window.Worker) { + console.log('Web Worker API not supported'); + // load index in main thread + $.getScript(joinUrl(base_url, "search/worker.js")).done(function () { + console.log('Loaded worker'); + init(); + window.postMessage = function (msg) { + onWorkerMessage({data: msg}); + }; + }).fail(function (jqxhr, settings, exception) { + console.error('Could not load worker.js'); + }); +} else { + // Wrap search in a web worker + var searchWorker = new Worker(joinUrl(base_url, "search/worker.js")); + searchWorker.postMessage({init: true}); + searchWorker.onmessage = onWorkerMessage; +} diff --git a/search/search_index.json b/search/search_index.json new file mode 100644 index 000000000..c064f9142 --- /dev/null +++ b/search/search_index.json @@ -0,0 +1 @@ +{"config":{"indexing":"full","lang":["en"],"min_search_length":3,"prebuild_index":false,"separator":"[\\s\\-]+"},"docs":[{"location":"","text":"Introduction Home battery prediction and automatic charging for Home Assistant with GivTCP Also known by some as Batpred or Batman! Copyright (c) Trefor Southwell October 2024 - All rights reserved This software maybe used at not cost for personal use only No warranty is given, either expressed or implied For support please raise a Github ticket or use the GivTCP Facebook page: https://www.facebook.com/groups/615579009972782 For support specific to the Solis inverter you can use the Solis Facebook Group: . If you want to buy me a beer then please use Paypal - tdlj@tdlj.net","title":"Introduction"},{"location":"#introduction","text":"Home battery prediction and automatic charging for Home Assistant with GivTCP Also known by some as Batpred or Batman! Copyright (c) Trefor Southwell October 2024 - All rights reserved This software maybe used at not cost for personal use only No warranty is given, either expressed or implied For support please raise a Github ticket or use the GivTCP Facebook page: https://www.facebook.com/groups/615579009972782 For support specific to the Solis inverter you can use the Solis Facebook Group: . If you want to buy me a beer then please use Paypal - tdlj@tdlj.net","title":"Introduction"},{"location":"apps-yaml/","text":"apps.yaml settings The basic configuration for Predbat is configured in the apps.yaml file. Depending on whether you have used the combined AppDaemon/Predbat add-on installation method or the HACS, Appdaemon add-on then Predbat installation method , the apps.yaml file will be held in one of two directories in Home Assistant: /addon_configs/46f69597_appdaemon-predbat/apps if you used the combined AppDaemon/Predbat add-on installation method or /config/appdaemon/apps/batpred/config/ if you used the HACS, AppDaemon add-on then Predbat installation method You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) to edit the apps.yaml file - see editing configuration files within Home Assistant if you need to install an editor. This section of the documentation describes what the different configuration items in apps.yaml do. When you edit apps.yaml , AppDaemon will automatically detect the change and Predbat will be reloaded with the updated file. You don't need to restart the AppDaemon add-on for your edits to take effect. Templates You can find template configurations in the following locations: Template Link GivEnergy apps.yaml SolisX apps.yaml SolarEdge apps.yaml The GivEnergy template will be installed by default but if you are using another inverter please copy the correct template into the directory where your apps.yaml is stored, and modify it from there. Basics Basic configuration items prefix - Set to the prefix name to be used for all entities that predbat creates in Home Assistant. Default 'predbat'. Unlikely that you will need to change this. timezone - Set to your local timezone, default is Europe/London. It must be set to a valid Python time zone for your location template - Initially set to True, this is used to stop Predbat from operating until you have finished configuring your apps.yaml. Once you have made all other required changes to apps.yaml this line should be deleted or commented out. notify_devices - A list of device names to notify when Predbat sends a notification. The default is just 'notify' which contacts all mobile devices days_previous - A list (one entry per line) of the number of days of historical house load to be used to predict your future daily load. It's recommended that you set days_previous so Predbat uses sufficient days' history so that 'unusual' load activity (e.g. saving sessions, \"big washing day\", etc) get averaged out. Typical settings could be 1, 7 or 7, 14, or 2, 3, 4, 5, 6, 7, 8. Do keep in mind that Home Assistant only keeps 10 days history by default, so you might need to increase the number of days history kept in HA before its purged by editing and adding the following to the /homeassistant/configuration.yaml configuration file and restarting Home Assistant afterwards: recorder: purge_keep_days: 14 days_previous_weight - A list (one entry per line) of weightings to be applied to each of the days in days_previous. Default value is 1, that all history days are equally weighted. forecast_hours - the number of hours to that Predbat will forecast ahead, 48 is the suggested amount, although other values can be used such as 30 or 36 if you have a small battery and thus don't need to forecast 2 days ahead. Inverter information The template apps.yaml comes pre-configured with regular expressions that should auto-discover the GivTCP Home Assistant entity names. If you have more than one inverter or entity names are non-standard then you will need to edit apps.yaml for your inverter entities. For other inverter brands, see Other Inverters num_inverters - The number of inverters you have. If you increase this above 1 you must provide multiple of each of the inverter entities geserial - This is a helper regular expression to find your serial number, if it doesn't work edit it manually or change individual entities to match. Historical data Predbat can either get historical data (house load, import, export and PV generation) directly from GivTCP or it can obtain it from the GivEnergy cloud. Unless you have a specific reason to not use the GivTCP data (e.g. you've lost your GivTCP data), its recommended to use GivTCP. Data from GivTCP The following configuration entries in apps.yaml are pre-configured to automatically use the appropriate GivTCP sensors. If you have a 3-phase electricity supply and one inverter (and battery) on each phase then you will need to add one line for the load, import, export and PV sensors for each of the 3 phases. If you have a single phase electricity supply and multiple inverters on the phase then you will need to add one line for each of the load and PV sensors. You don't need multiple lines for the import or export sensors as each inverter will give the total import or export information. Edit if necessary if you have non-standard GivTCP sensor names: load_today - GivTCP Entity name for the house load in kWh today (must be incrementing) import_today - GivTCP Imported energy today in kWh (incrementing) export_today - GivTCP Exported energy today in kWh (incrementing) pv_today - GivTCP PV energy today in kWh (incrementing). If you have multiple inverters, enter each inverter PV sensor on a separate line. If you have an AC-coupled GivEnergy inverter then enter the Home Assistant sensor for your PV inverter. If you don't have any PV panels, comment or delete this line out of apps.yaml. See the Workarounds section below for configuration settings for scaling these if required. If you have multiple inverters then you may find that the load_today figures from GivTCP are incorrect as the inverters share the house load between them. In this circumstance one solution is to create a Home Assistant template helper to calculate house load from {pv generation}+{battery discharge}-{battery charge}+{import}-{export}. e.g. {{ states('sensor.givtcp_XXX_pv_energy_today_kwh')|float(0) + ... + states('sensor.givtcp_XXX_battery_discharge_energy_today_kwh')|float(0) + ... - states('sensor.givtcp_XXX_battery_charge_energy_today_kwh')|float(0) - ... + states('sensor.givtcp_XXX_import_energy_today_kwh')|float(0) - states('sensor.givtcp_XXX_export_energy_today_kwh')|float(0) }} GivEnergy Cloud Data If you have an issue with the GivTCP data, Predbat can get the required historical data from the GivEnergy cloud instead. This data is updated every 30 minutes. Obviously connecting to the cloud is less efficient and means that Predbat will be dependent upon your internet connection and the GivEnergy cloud to operate. ge_cloud_data - When True Predbat will use the GE Cloud for data rather than load_today, import_today and export_today ge_cloud_serial - Set the inverter serial number to use for the Cloud data ge_cloud_key - Set to your API Key for the GE Cloud (long string) Load filtering By default if Predbat sees a gap in the historical load data it will fill it with average data. This is to help in the cases of small amounts of lost data. For entire lost days you should change days_previous to point to different days(s) or include 3 or more days and if you set switch.predbat_load_filter_modal to true, the lowest day's historical load will be discarded. load_filter_threshold - Sets the number of minutes of zero load data to be considered a gap (that's filled with average data), the default is 30. To disable, set it to 1440. Inverter control configurations inverter_limit - One per inverter. When set defines the maximum watts of AC output power for your inverter (e.g. 3600). This will help to emulate clipping when your solar produces more than the inverter can handle, but it won't be that accurate as the source of the data isn't minute by minute. If you have a separate Solar inverter as well then add the solar inverter limit to the battery inverter limit to give one total amount. export_limit - One per inverter (optional). When set defines the maximum watts of AC power your inverter can export to the grid at (e.g. 2500). This will emulate the software export limit setting in the Inverter that you will have if your G98/G99 approval was lower than your maximum inverter power (check your install information for details). If you do not set an export limit then it's the same as the inverter limit. inverter_limit_charge and inverter_limit_discharge - One per inverter (optional). When set in watts, overrides the maximum charge/discharge rate settings used when controlling the inverter. This can be used if you need to cap your inverter battery rate (e.g. charge overnight at a slower rate to reduce inverter/battery heating) as Predbat will normally configure all timed charges or discharges to be at the inverter's maximum rate. Controlling the Inverter There are two ways that Predbat can control GivTCP to control the inverter, either via REST API calls (preferred) or via the GivTCP inverter controls in Home Assistant. REST Interface inverter control givtcp_rest - One per Inverter, sets the GivTCP REST API URL ( http://homeassistant.local:6345 is the normal one for the first inverter and :6346 for the second inverter). When enabled the Control per inverter below isn't used and instead communication from Predbat to GivTCP is directly via REST and thus bypasses some issues with MQTT. If using Docker then change homeassistant.local to the Docker IP address. To check your REST is working open up the readData API point in a Web browser e.g: http://homeassistant.local:6345/readData If you get a bunch of inverter information back then it's working! It's recommended you enable 'Output Raw Register Values' in GivTCP (via Settings / Add-on's / GivTCP / configuration tab) for added monitoring: Home Assistant inverter control As an alternative to REST control, Predbat can control the GivEnergy inverters via GivTCP controls in Home Assistant. The template apps.yaml is pre-configured with regular expressions for the following configuration items that should auto-discover the GivTCP controls, but may need changing if you have multiple inverters or non-standard GivTCP entity names. The givtcp_rest line should be commented out/deleted in order for Predbat to use the direct GivTCP Home Assistant controls. charge_rate - GivTCP battery charge rate entity in watts discharge_rate - GivTCP battery discharge max rate entity in watts battery_power - GivTCP current battery power in watts pv_power - GivTCP current PV power in watts load_power - GivTCP current load power in watts soc_kw - GivTCP Entity name of the battery SOC in kWh, should be the inverter one not an individual battery soc_max - GivTCP Entity name for the maximum charge level for the battery reserve - GivTCP sensor name for the reserve setting in % inverter_mode - GivTCP inverter mode control inverter_time - GivTCP inverter timestamp charge_start_time - GivTCP battery charge start time entity charge_end_time - GivTCP battery charge end time entity charge_limit - GivTCP Entity name for used to set the SOC target for the battery in percentage scheduled_charge_enable - GivTCP Scheduled charge enable config scheduled_discharge_enable - GivTCP Scheduled discharge enable config discharge_start_time - GivTCP scheduled discharge slot_1 start time discharge_end_time - GivTCP scheduled discharge slot_1 end time If you are using REST control the above GivTCP configuration items can be deleted or commented out of apps.yaml. Solcast Solar Forecast As described in the Predbat installation instructions , Predbat needs a solar forecast in order to predict solar generation and battery charging which can be provided by the Solcast integration. The template apps.yaml is pre-configured with regular expressions for the following configuration items that should auto-discover the Solcast entity names. They are unlikely to need changing although a few people have reported their entity names don't contain 'solcast' so worth checking, or edit if you have non-standard names: pv_forecast_today - Entity name for today's Solcast forecast pv_forecast_tomorrow - Entity name for tomorrow's Solcast's forecast pv_forecast_d3 - Entity name for Solcast's forecast for day 3 pv_forecast_d4 - Entity name for Solcast's forecast for day 4 (also d5, d6 & d7 are supported, but not that useful) If you do not have a PV array then comment out or delete these Solcast lines from apps.yaml . If you have multiple PV arrays connected to GivEnergy Hybrid inverters or you have GivEnergy AC-coupled inverters, then ensure your PV configuration in Solcast covers all arrays. If however you have a mixed PV array setup with some PV that does not feed into your GivEnergy inverters (e.g. hybrid GE inverters but a separate older FIT array that directly feeds AC into the house), then it's recommended that Solcast is only configured for the PV connected to the GivEnergy inverters. Solcast produces 3 forecasted PV estimates, the 'central' (50% or most likely to occur) PV forecast, the '10%' (worst case) PV forecast, and the '90%' (best case) PV forecast. By default Predbat will use the central estimate and applies to it the input_number.pv_metric10_weight weighting of the 10% (worst case) estimate. Predbat models cloud coverage by using the difference between the PV and PV10 forecasts to work out a cloud factor, this modulates the PV output predictions up and down accordingly as if there were passing clouds. This can have an impact on planning, especially for things like freeze charging which could assume the PV will cover the house load but it might not due to clouds. pv_estimate in apps.yaml can be used to configure Predbat to always use the 10% forecast by setting the configuration item to '10', or '90' to always use the 90% PV estimate (not recommended!). Set to blank or delete / comment out the line to use the default central estimate. If pv_estimate is set to 10 then input_number.pv_metric10_weight in Home Assistant should be set to 1.0. Energy Rates There are a number of configuration items in apps.yaml for telling Predbat what your import and export rates are. These are described in detail in Energy Rates and are listed here just for completeness: metric_octopus_import - Import rates from the Octopus Energy integration metric_octopus_export - Export rates from the Octopus Energy integration metric_octopus_gas - Gas rates from the Octopus Energy integration octopus_intelligent_slot - Octopus Intelligent GO slot sensor from the Octopus Energy integration octopus_saving_session - Energy saving sessions sensor from the Octopus Energy integration octopus_saving_session_octopoints_per_penny - Sets the Octopoints per pence rates_import_octopus_url - Octopus pricing URL (over-rides metric_octopus_import) rates_export_octopus_url - Octopus export pricing URL (over-rides metric_octopus_export) metric_standing_charge - Standing charge in pounds rates_import - Import rates over a 24-hour period with start and end times rates_export - Export rates over a 24-hour period with start and end times rates_import_override - Over-ride import rate for specific date and time range, e.g. Octopus Power-up events rates_export_override - Over-ride export rate for specific date and time range futurerate_url - URL of future energy market prices for Agile users futurerate_adjust_import and futurerate_adjust_export - Whether tomorrow's predicted import or export prices should be adjusted based on market prices or not futurerate_peak_start and futurerate_peak_end - start/end times for peak-rate adjustment futurerate_peak_premium_import and futurerate_peak_premium_export - price premium to be added during the peak period Car Charging Integration Predbat is able to include electric vehicle charging in its plan and manage the battery activity so that the battery isn't discharged into your car when the car is charging (although you can over-ride this if you wish by setting the switch.predbat_car_charging_from_battery to True in Home Assistant). There are two different ways of planning car charging into cheap slots with Predbat, either by the Octopus Energy integration or by Predbat identifying the cheapest slots. These approaches and the set of settings that need to be configured together are described in Car Charging Planning . The full list of car charging configuration items in apps.yaml that are used to plan car charging activity within Predbat are described below. The Home Assistant controls (switches, input numbers, selectors, etc) related to car charging are described in Car Charging configuration within Home Assistant , with brief mention of pertinent controls included here alongside the apps.yaml configuration items where relevant for context. num_cars should be set in apps.yaml to the number of cars you want Predbat to plan for. Set to 0 if you don't have an EV (and the remaining car sensors in apps.yaml can safely be commented out or deleted as they won't be required). Car Charging Filtering You might want to remove your electric car charging data from the historical house load data so as to not bias the calculations, otherwise you will get high battery charge levels when the car was charged previously (e.g. last week). switch.car_charging_hold - A Home Assistant switch that when turned on (True) tells Predbat to remove car charging data from Predbat's battery prediction plan. car_charging_energy - Set in apps.yaml to point to a Home Assistant entity which is the incrementing kWh data for the car charger. This has been pre-defined to a regular expression to auto-detect the appropriate Wallbox and Zappi car charger sensors, or edit as necessary in apps.yaml for your charger sensor. input_number.car_charging_energy_scale - A Home Assistant entity used to define a scaling factor (in the range 0.1 to 1.0) to multiply the car_charging_energy data by if required (e.g. set to 0.001 to convert Watts to kW). If you do not have a suitable car charging kWh sensor in Home Assistant then comment the car_charging_energy line out of apps.yaml and configure the following Home Assistant entity: input_number.car_charging_threshold - Sets the threshold above which home consumption is assumed to be car charging and will be removed from the home load data (default 6 = 6kW). Planned Car Charging These features allow Predbat to know when you plan to charge your car. If you have Intelligent Octopus setup then planning of charging is done via the Octopus app and Predbat obtains this information through the Octopus Energy integration in Home Assistant. switch.predbat_octopus_intelligent_charging - When this Home Assistant switch is enabled, Predbat will plan charging around the Intelligent Octopus slots, taking it into account for battery load and generating the slot information The following apps.yaml configuration items are pre-defined with regular expressions to point to appropriate sensors in the Octopus Energy integration. You should not normally need to change these if you have Octopus Intelligent: octopus_intelligent_slot - Points to the Octopus Energy integration 'intelligent dispatching' sensor that indicates whether you are within an Octopus Energy \"smart charge\" slot, and provides the list of future planned charging activity. octopus_ready_time - Points to the Octopus Energy integration sensor that details when the car charging will be completed by. octopus_charge_limit - Points to the Octopus Energy integration sensor that provides the car charging limit. If you don't use Intelligent Octopus then the above 3 Octopus Intelligent configuration lines in apps.yaml can be commented out or deleted, and there are a number of other apps.yaml configuration items that should be set: car_charging_planned - Optional, can be set to a Home Assistant sensor which lets Predbat know the car is plugged in and planned to charge during low rate slots. Or manually set it to 'False' to disable this feature, or 'True' to always enable. car_charging_planned_response - An array of values for the above car_charging_planned sensor which indicate that the car is plugged in and will charge in the next low rate slot. Customise for your car charger sensor if it sets sensor values that are not in the pre-defined list. car_charging_now - For some cases finding details of planned car charging is difficult to obtain (e.g. Ohme with Intelligent doesn't report slots). The car_charging_now configuration item can be set to point to a Home Assistant sensor that tells you that the car is currently charging. Predbat will then assume this 30 minute slot is used for charging regardless of the plan. If Octopus Intelligent Charging is enabled and car_charging_now indicates the car is charging then Predbat will also assume that this is a low rate slot for the car/house (and might therefore start charging the battery), otherwise electricity import rates are taken from the normal rate data. car_charging_now_response - Set to the range of positive responses for car_charging_now to indicate that the car is charging. Useful if you have a sensor for your car charger that isn't binary. To make planned car charging more accurate, configure the following items in apps.yaml : car_charging_battery_size - Set to the car's battery size in kWh, defaults to 100. It will be used to predict car charging stops. car_charging_limit - Set to point to a sensor that specifies the % limit the car is set to charge to. Default is 100% car_charging_soc - Set to point to a sensor that specifies the car's current % charge level. Default is 0% Multiple Electric Cars Multiple cars can be planned with Predbat, in which case you should set num_cars in apps.yaml to the number of cars you want to plan car_charging_limit , car_charging_planned , car_charging_battery_size and car_charging_soc must then be a list of values (i.e. 2 entries for 2 cars) If you have Intelligent Octopus then Car 0 will be managed by the Octopus Energy integration, if its enabled Each car will have it's own Home Assistant slot sensor created e.g. binary_sensor.predbat_car_charging_slot_1 , SOC planning sensor e.g predbat.car_soc_1 and predbat.car_soc_best_1 for car 1 Balance Inverters When you have two or more inverters it's possible they get out of sync so they are at different charge levels or they start to cross-charge (one discharges into another). When enabled, balance inverters tries to recover this situation by disabling either charging or discharging from one of the batteries until they re-align. Most of the Predbat configuration for balancing inverters is through a number of Home Assistant controls for Balancing Inverters , but there is one configuration item in apps.yaml : balance_inverters_seconds - defines how often to run the inverter balancing, 30 seconds is recommended if your machine is fast enough, but the default is 60 seconds. Workarounds There are a number of different configuration items in apps.yaml that can be used to tweak the way Predbat operates and workaround weirdness you may have from your inverter and battery setup. clock_skew - Skews the local (computer) time that Predbat uses (from AppDaemon). Set to 1 means add a minute to the AppDaemon time, set to -1 means take a minute off the AppDaemon time. This will change when real-time actions happen e.g. triggering a charge or discharge. If your inverter's time is different to the time on the computer running Home Assistant, you may need to skew the time settings made on the inverter when you trigger charging or discharging. Again 1 means the inverter is 1 minute fast and -1 means the inverter is 1 minute slow. Separate start and end options are applied to the start and end time windows, mostly as you want to start battery activity late (not early) and finish early (not late). You can adjust the charge and discharge times written to the inverter by setting the following in apps.yaml : inverter_clock_skew_start , inverter_clock_skew_end - Skews the setting of the charge slot registers vs the predicted start time inverter_clock_skew_discharge_start , inverter_clock_skew_discharge_end - Skews the setting of the discharge slot registers vs the predicted start time battery_scaling - Default value 1.0. This setting is used to scale the battery reported SOC kWh to make it appear bigger or larger than it is e.g. if you have an 80% depth of discharge battery that falsely reports its capacity, set this to 0.8 to report the real figure. If you are going chart your battery SoC in Home Assistant then you may want to use predbat.soc_kw_h0 as your current SoC rather than the usual givtcp_ _soc GivTCP entity so everything lines up import_export_scaling - Default value 1.0. Used to scale the import & export kWh data from GivTCP if the inverter information is incorrect. inverter_battery_rate_min - One per inverter (optional), set in Watts, when set models a \"bug\" in the inverter firmware in some models where if charge or discharge rates are set to 0 you actually get a small amount of charge or discharge. Recommended setting is 200 for Gen 1 hybrids with this issue. inverter_reserve_max - Global, sets the maximum reserve % that maybe set to the inverter, the default is 98 as some Gen 2 inverters and AIO firmware versions refuse to be set to 100. Comment the line out or set to 100 if your inverter allows setting to 100%. battery_charge_power_curve - Some batteries tail off their charge rate at high soc% and this optional configuration item enables you to model this in Predbat. Enter the charging curve as a series of steps of % of max charge rate for each soc percentage. The default is 1.0 (full power) charge all the way to 100%. Example from a GivEnergy 9.5kWh battery with latest firmware and Gen 1 inverter: battery_charge_power_curve: 91 : 0.91 92 : 0.81 93 : 0.71 94 : 0.62 95 : 0.52 96 : 0.43 97 : 0.33 98 : 0.24 99 : 0.24 100 : 0.24 Triggers The trigger feature is useful to help trigger your own automations based on Predbat determining that you have spare solar energy or battery that you would otherwise export. For example you may turn an immersion heater or the washing machine on to consume the excess solar power. The triggers count export energy until the next active charge slot only. For each trigger give a name, the minutes of export needed and the energy required in that time. Multiple triggers can be set at once so in total you could use too much energy if all run. Each trigger specified in apps.yaml will create a Home Assistant entity called 'binary_sensor.predbat_export_trigger_ name ' which will be turned on when the condition is valid. Connect this binary sensor to your automation to start whatever you want to trigger. Set the name for each trigger, the number of minutes of solar export you need, and the amount of energy in kWh you will need available during that time period in apps.yaml: For example: export_triggers: - name: \"large\" minutes: 60 energy: 1.0 - name: \"small\" minutes: 15 energy: 0.25 If you wish to trigger based on charging or discharging the battery rather than spare solar energy you can instead use the following binary sensors in Home Assistant: binary_sensor.predbat_charging - Will be True when the home battery is inside a charge slot (either being charged or being held at a level). Note that this does include charge freeze slots where the discharge rate is set to zero without charging the battery. binary_sensor.predbat_discharging - Will be True when the home battery is inside a force discharge slot. This does not include discharge freeze slots where the charge rate is set to zero to export excess solar only.","title":"apps.yaml settings"},{"location":"apps-yaml/#appsyaml-settings","text":"The basic configuration for Predbat is configured in the apps.yaml file. Depending on whether you have used the combined AppDaemon/Predbat add-on installation method or the HACS, Appdaemon add-on then Predbat installation method , the apps.yaml file will be held in one of two directories in Home Assistant: /addon_configs/46f69597_appdaemon-predbat/apps if you used the combined AppDaemon/Predbat add-on installation method or /config/appdaemon/apps/batpred/config/ if you used the HACS, AppDaemon add-on then Predbat installation method You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) to edit the apps.yaml file - see editing configuration files within Home Assistant if you need to install an editor. This section of the documentation describes what the different configuration items in apps.yaml do. When you edit apps.yaml , AppDaemon will automatically detect the change and Predbat will be reloaded with the updated file. You don't need to restart the AppDaemon add-on for your edits to take effect.","title":"apps.yaml settings"},{"location":"apps-yaml/#templates","text":"You can find template configurations in the following locations: Template Link GivEnergy apps.yaml SolisX apps.yaml SolarEdge apps.yaml The GivEnergy template will be installed by default but if you are using another inverter please copy the correct template into the directory where your apps.yaml is stored, and modify it from there.","title":"Templates"},{"location":"apps-yaml/#basics","text":"Basic configuration items prefix - Set to the prefix name to be used for all entities that predbat creates in Home Assistant. Default 'predbat'. Unlikely that you will need to change this. timezone - Set to your local timezone, default is Europe/London. It must be set to a valid Python time zone for your location template - Initially set to True, this is used to stop Predbat from operating until you have finished configuring your apps.yaml. Once you have made all other required changes to apps.yaml this line should be deleted or commented out. notify_devices - A list of device names to notify when Predbat sends a notification. The default is just 'notify' which contacts all mobile devices days_previous - A list (one entry per line) of the number of days of historical house load to be used to predict your future daily load. It's recommended that you set days_previous so Predbat uses sufficient days' history so that 'unusual' load activity (e.g. saving sessions, \"big washing day\", etc) get averaged out. Typical settings could be 1, 7 or 7, 14, or 2, 3, 4, 5, 6, 7, 8. Do keep in mind that Home Assistant only keeps 10 days history by default, so you might need to increase the number of days history kept in HA before its purged by editing and adding the following to the /homeassistant/configuration.yaml configuration file and restarting Home Assistant afterwards: recorder: purge_keep_days: 14 days_previous_weight - A list (one entry per line) of weightings to be applied to each of the days in days_previous. Default value is 1, that all history days are equally weighted. forecast_hours - the number of hours to that Predbat will forecast ahead, 48 is the suggested amount, although other values can be used such as 30 or 36 if you have a small battery and thus don't need to forecast 2 days ahead.","title":"Basics"},{"location":"apps-yaml/#inverter-information","text":"The template apps.yaml comes pre-configured with regular expressions that should auto-discover the GivTCP Home Assistant entity names. If you have more than one inverter or entity names are non-standard then you will need to edit apps.yaml for your inverter entities. For other inverter brands, see Other Inverters num_inverters - The number of inverters you have. If you increase this above 1 you must provide multiple of each of the inverter entities geserial - This is a helper regular expression to find your serial number, if it doesn't work edit it manually or change individual entities to match.","title":"Inverter information"},{"location":"apps-yaml/#historical-data","text":"Predbat can either get historical data (house load, import, export and PV generation) directly from GivTCP or it can obtain it from the GivEnergy cloud. Unless you have a specific reason to not use the GivTCP data (e.g. you've lost your GivTCP data), its recommended to use GivTCP.","title":"Historical data"},{"location":"apps-yaml/#data-from-givtcp","text":"The following configuration entries in apps.yaml are pre-configured to automatically use the appropriate GivTCP sensors. If you have a 3-phase electricity supply and one inverter (and battery) on each phase then you will need to add one line for the load, import, export and PV sensors for each of the 3 phases. If you have a single phase electricity supply and multiple inverters on the phase then you will need to add one line for each of the load and PV sensors. You don't need multiple lines for the import or export sensors as each inverter will give the total import or export information. Edit if necessary if you have non-standard GivTCP sensor names: load_today - GivTCP Entity name for the house load in kWh today (must be incrementing) import_today - GivTCP Imported energy today in kWh (incrementing) export_today - GivTCP Exported energy today in kWh (incrementing) pv_today - GivTCP PV energy today in kWh (incrementing). If you have multiple inverters, enter each inverter PV sensor on a separate line. If you have an AC-coupled GivEnergy inverter then enter the Home Assistant sensor for your PV inverter. If you don't have any PV panels, comment or delete this line out of apps.yaml. See the Workarounds section below for configuration settings for scaling these if required. If you have multiple inverters then you may find that the load_today figures from GivTCP are incorrect as the inverters share the house load between them. In this circumstance one solution is to create a Home Assistant template helper to calculate house load from {pv generation}+{battery discharge}-{battery charge}+{import}-{export}. e.g. {{ states('sensor.givtcp_XXX_pv_energy_today_kwh')|float(0) + ... + states('sensor.givtcp_XXX_battery_discharge_energy_today_kwh')|float(0) + ... - states('sensor.givtcp_XXX_battery_charge_energy_today_kwh')|float(0) - ... + states('sensor.givtcp_XXX_import_energy_today_kwh')|float(0) - states('sensor.givtcp_XXX_export_energy_today_kwh')|float(0) }}","title":"Data from GivTCP"},{"location":"apps-yaml/#givenergy-cloud-data","text":"If you have an issue with the GivTCP data, Predbat can get the required historical data from the GivEnergy cloud instead. This data is updated every 30 minutes. Obviously connecting to the cloud is less efficient and means that Predbat will be dependent upon your internet connection and the GivEnergy cloud to operate. ge_cloud_data - When True Predbat will use the GE Cloud for data rather than load_today, import_today and export_today ge_cloud_serial - Set the inverter serial number to use for the Cloud data ge_cloud_key - Set to your API Key for the GE Cloud (long string)","title":"GivEnergy Cloud Data"},{"location":"apps-yaml/#load-filtering","text":"By default if Predbat sees a gap in the historical load data it will fill it with average data. This is to help in the cases of small amounts of lost data. For entire lost days you should change days_previous to point to different days(s) or include 3 or more days and if you set switch.predbat_load_filter_modal to true, the lowest day's historical load will be discarded. load_filter_threshold - Sets the number of minutes of zero load data to be considered a gap (that's filled with average data), the default is 30. To disable, set it to 1440.","title":"Load filtering"},{"location":"apps-yaml/#inverter-control-configurations","text":"inverter_limit - One per inverter. When set defines the maximum watts of AC output power for your inverter (e.g. 3600). This will help to emulate clipping when your solar produces more than the inverter can handle, but it won't be that accurate as the source of the data isn't minute by minute. If you have a separate Solar inverter as well then add the solar inverter limit to the battery inverter limit to give one total amount. export_limit - One per inverter (optional). When set defines the maximum watts of AC power your inverter can export to the grid at (e.g. 2500). This will emulate the software export limit setting in the Inverter that you will have if your G98/G99 approval was lower than your maximum inverter power (check your install information for details). If you do not set an export limit then it's the same as the inverter limit. inverter_limit_charge and inverter_limit_discharge - One per inverter (optional). When set in watts, overrides the maximum charge/discharge rate settings used when controlling the inverter. This can be used if you need to cap your inverter battery rate (e.g. charge overnight at a slower rate to reduce inverter/battery heating) as Predbat will normally configure all timed charges or discharges to be at the inverter's maximum rate.","title":"Inverter control configurations"},{"location":"apps-yaml/#controlling-the-inverter","text":"There are two ways that Predbat can control GivTCP to control the inverter, either via REST API calls (preferred) or via the GivTCP inverter controls in Home Assistant.","title":"Controlling the Inverter"},{"location":"apps-yaml/#rest-interface-inverter-control","text":"givtcp_rest - One per Inverter, sets the GivTCP REST API URL ( http://homeassistant.local:6345 is the normal one for the first inverter and :6346 for the second inverter). When enabled the Control per inverter below isn't used and instead communication from Predbat to GivTCP is directly via REST and thus bypasses some issues with MQTT. If using Docker then change homeassistant.local to the Docker IP address. To check your REST is working open up the readData API point in a Web browser e.g: http://homeassistant.local:6345/readData If you get a bunch of inverter information back then it's working! It's recommended you enable 'Output Raw Register Values' in GivTCP (via Settings / Add-on's / GivTCP / configuration tab) for added monitoring:","title":"REST Interface inverter control"},{"location":"apps-yaml/#home-assistant-inverter-control","text":"As an alternative to REST control, Predbat can control the GivEnergy inverters via GivTCP controls in Home Assistant. The template apps.yaml is pre-configured with regular expressions for the following configuration items that should auto-discover the GivTCP controls, but may need changing if you have multiple inverters or non-standard GivTCP entity names. The givtcp_rest line should be commented out/deleted in order for Predbat to use the direct GivTCP Home Assistant controls. charge_rate - GivTCP battery charge rate entity in watts discharge_rate - GivTCP battery discharge max rate entity in watts battery_power - GivTCP current battery power in watts pv_power - GivTCP current PV power in watts load_power - GivTCP current load power in watts soc_kw - GivTCP Entity name of the battery SOC in kWh, should be the inverter one not an individual battery soc_max - GivTCP Entity name for the maximum charge level for the battery reserve - GivTCP sensor name for the reserve setting in % inverter_mode - GivTCP inverter mode control inverter_time - GivTCP inverter timestamp charge_start_time - GivTCP battery charge start time entity charge_end_time - GivTCP battery charge end time entity charge_limit - GivTCP Entity name for used to set the SOC target for the battery in percentage scheduled_charge_enable - GivTCP Scheduled charge enable config scheduled_discharge_enable - GivTCP Scheduled discharge enable config discharge_start_time - GivTCP scheduled discharge slot_1 start time discharge_end_time - GivTCP scheduled discharge slot_1 end time If you are using REST control the above GivTCP configuration items can be deleted or commented out of apps.yaml.","title":"Home Assistant inverter control"},{"location":"apps-yaml/#solcast-solar-forecast","text":"As described in the Predbat installation instructions , Predbat needs a solar forecast in order to predict solar generation and battery charging which can be provided by the Solcast integration. The template apps.yaml is pre-configured with regular expressions for the following configuration items that should auto-discover the Solcast entity names. They are unlikely to need changing although a few people have reported their entity names don't contain 'solcast' so worth checking, or edit if you have non-standard names: pv_forecast_today - Entity name for today's Solcast forecast pv_forecast_tomorrow - Entity name for tomorrow's Solcast's forecast pv_forecast_d3 - Entity name for Solcast's forecast for day 3 pv_forecast_d4 - Entity name for Solcast's forecast for day 4 (also d5, d6 & d7 are supported, but not that useful) If you do not have a PV array then comment out or delete these Solcast lines from apps.yaml . If you have multiple PV arrays connected to GivEnergy Hybrid inverters or you have GivEnergy AC-coupled inverters, then ensure your PV configuration in Solcast covers all arrays. If however you have a mixed PV array setup with some PV that does not feed into your GivEnergy inverters (e.g. hybrid GE inverters but a separate older FIT array that directly feeds AC into the house), then it's recommended that Solcast is only configured for the PV connected to the GivEnergy inverters. Solcast produces 3 forecasted PV estimates, the 'central' (50% or most likely to occur) PV forecast, the '10%' (worst case) PV forecast, and the '90%' (best case) PV forecast. By default Predbat will use the central estimate and applies to it the input_number.pv_metric10_weight weighting of the 10% (worst case) estimate. Predbat models cloud coverage by using the difference between the PV and PV10 forecasts to work out a cloud factor, this modulates the PV output predictions up and down accordingly as if there were passing clouds. This can have an impact on planning, especially for things like freeze charging which could assume the PV will cover the house load but it might not due to clouds. pv_estimate in apps.yaml can be used to configure Predbat to always use the 10% forecast by setting the configuration item to '10', or '90' to always use the 90% PV estimate (not recommended!). Set to blank or delete / comment out the line to use the default central estimate. If pv_estimate is set to 10 then input_number.pv_metric10_weight in Home Assistant should be set to 1.0.","title":"Solcast Solar Forecast"},{"location":"apps-yaml/#energy-rates","text":"There are a number of configuration items in apps.yaml for telling Predbat what your import and export rates are. These are described in detail in Energy Rates and are listed here just for completeness: metric_octopus_import - Import rates from the Octopus Energy integration metric_octopus_export - Export rates from the Octopus Energy integration metric_octopus_gas - Gas rates from the Octopus Energy integration octopus_intelligent_slot - Octopus Intelligent GO slot sensor from the Octopus Energy integration octopus_saving_session - Energy saving sessions sensor from the Octopus Energy integration octopus_saving_session_octopoints_per_penny - Sets the Octopoints per pence rates_import_octopus_url - Octopus pricing URL (over-rides metric_octopus_import) rates_export_octopus_url - Octopus export pricing URL (over-rides metric_octopus_export) metric_standing_charge - Standing charge in pounds rates_import - Import rates over a 24-hour period with start and end times rates_export - Export rates over a 24-hour period with start and end times rates_import_override - Over-ride import rate for specific date and time range, e.g. Octopus Power-up events rates_export_override - Over-ride export rate for specific date and time range futurerate_url - URL of future energy market prices for Agile users futurerate_adjust_import and futurerate_adjust_export - Whether tomorrow's predicted import or export prices should be adjusted based on market prices or not futurerate_peak_start and futurerate_peak_end - start/end times for peak-rate adjustment futurerate_peak_premium_import and futurerate_peak_premium_export - price premium to be added during the peak period","title":"Energy Rates"},{"location":"apps-yaml/#car-charging-integration","text":"Predbat is able to include electric vehicle charging in its plan and manage the battery activity so that the battery isn't discharged into your car when the car is charging (although you can over-ride this if you wish by setting the switch.predbat_car_charging_from_battery to True in Home Assistant). There are two different ways of planning car charging into cheap slots with Predbat, either by the Octopus Energy integration or by Predbat identifying the cheapest slots. These approaches and the set of settings that need to be configured together are described in Car Charging Planning . The full list of car charging configuration items in apps.yaml that are used to plan car charging activity within Predbat are described below. The Home Assistant controls (switches, input numbers, selectors, etc) related to car charging are described in Car Charging configuration within Home Assistant , with brief mention of pertinent controls included here alongside the apps.yaml configuration items where relevant for context. num_cars should be set in apps.yaml to the number of cars you want Predbat to plan for. Set to 0 if you don't have an EV (and the remaining car sensors in apps.yaml can safely be commented out or deleted as they won't be required).","title":"Car Charging Integration"},{"location":"apps-yaml/#car-charging-filtering","text":"You might want to remove your electric car charging data from the historical house load data so as to not bias the calculations, otherwise you will get high battery charge levels when the car was charged previously (e.g. last week). switch.car_charging_hold - A Home Assistant switch that when turned on (True) tells Predbat to remove car charging data from Predbat's battery prediction plan. car_charging_energy - Set in apps.yaml to point to a Home Assistant entity which is the incrementing kWh data for the car charger. This has been pre-defined to a regular expression to auto-detect the appropriate Wallbox and Zappi car charger sensors, or edit as necessary in apps.yaml for your charger sensor. input_number.car_charging_energy_scale - A Home Assistant entity used to define a scaling factor (in the range 0.1 to 1.0) to multiply the car_charging_energy data by if required (e.g. set to 0.001 to convert Watts to kW). If you do not have a suitable car charging kWh sensor in Home Assistant then comment the car_charging_energy line out of apps.yaml and configure the following Home Assistant entity: input_number.car_charging_threshold - Sets the threshold above which home consumption is assumed to be car charging and will be removed from the home load data (default 6 = 6kW).","title":"Car Charging Filtering"},{"location":"apps-yaml/#planned-car-charging","text":"These features allow Predbat to know when you plan to charge your car. If you have Intelligent Octopus setup then planning of charging is done via the Octopus app and Predbat obtains this information through the Octopus Energy integration in Home Assistant. switch.predbat_octopus_intelligent_charging - When this Home Assistant switch is enabled, Predbat will plan charging around the Intelligent Octopus slots, taking it into account for battery load and generating the slot information The following apps.yaml configuration items are pre-defined with regular expressions to point to appropriate sensors in the Octopus Energy integration. You should not normally need to change these if you have Octopus Intelligent: octopus_intelligent_slot - Points to the Octopus Energy integration 'intelligent dispatching' sensor that indicates whether you are within an Octopus Energy \"smart charge\" slot, and provides the list of future planned charging activity. octopus_ready_time - Points to the Octopus Energy integration sensor that details when the car charging will be completed by. octopus_charge_limit - Points to the Octopus Energy integration sensor that provides the car charging limit. If you don't use Intelligent Octopus then the above 3 Octopus Intelligent configuration lines in apps.yaml can be commented out or deleted, and there are a number of other apps.yaml configuration items that should be set: car_charging_planned - Optional, can be set to a Home Assistant sensor which lets Predbat know the car is plugged in and planned to charge during low rate slots. Or manually set it to 'False' to disable this feature, or 'True' to always enable. car_charging_planned_response - An array of values for the above car_charging_planned sensor which indicate that the car is plugged in and will charge in the next low rate slot. Customise for your car charger sensor if it sets sensor values that are not in the pre-defined list. car_charging_now - For some cases finding details of planned car charging is difficult to obtain (e.g. Ohme with Intelligent doesn't report slots). The car_charging_now configuration item can be set to point to a Home Assistant sensor that tells you that the car is currently charging. Predbat will then assume this 30 minute slot is used for charging regardless of the plan. If Octopus Intelligent Charging is enabled and car_charging_now indicates the car is charging then Predbat will also assume that this is a low rate slot for the car/house (and might therefore start charging the battery), otherwise electricity import rates are taken from the normal rate data. car_charging_now_response - Set to the range of positive responses for car_charging_now to indicate that the car is charging. Useful if you have a sensor for your car charger that isn't binary. To make planned car charging more accurate, configure the following items in apps.yaml : car_charging_battery_size - Set to the car's battery size in kWh, defaults to 100. It will be used to predict car charging stops. car_charging_limit - Set to point to a sensor that specifies the % limit the car is set to charge to. Default is 100% car_charging_soc - Set to point to a sensor that specifies the car's current % charge level. Default is 0%","title":"Planned Car Charging"},{"location":"apps-yaml/#multiple-electric-cars","text":"Multiple cars can be planned with Predbat, in which case you should set num_cars in apps.yaml to the number of cars you want to plan car_charging_limit , car_charging_planned , car_charging_battery_size and car_charging_soc must then be a list of values (i.e. 2 entries for 2 cars) If you have Intelligent Octopus then Car 0 will be managed by the Octopus Energy integration, if its enabled Each car will have it's own Home Assistant slot sensor created e.g. binary_sensor.predbat_car_charging_slot_1 , SOC planning sensor e.g predbat.car_soc_1 and predbat.car_soc_best_1 for car 1","title":"Multiple Electric Cars"},{"location":"apps-yaml/#balance-inverters","text":"When you have two or more inverters it's possible they get out of sync so they are at different charge levels or they start to cross-charge (one discharges into another). When enabled, balance inverters tries to recover this situation by disabling either charging or discharging from one of the batteries until they re-align. Most of the Predbat configuration for balancing inverters is through a number of Home Assistant controls for Balancing Inverters , but there is one configuration item in apps.yaml : balance_inverters_seconds - defines how often to run the inverter balancing, 30 seconds is recommended if your machine is fast enough, but the default is 60 seconds.","title":"Balance Inverters"},{"location":"apps-yaml/#workarounds","text":"There are a number of different configuration items in apps.yaml that can be used to tweak the way Predbat operates and workaround weirdness you may have from your inverter and battery setup. clock_skew - Skews the local (computer) time that Predbat uses (from AppDaemon). Set to 1 means add a minute to the AppDaemon time, set to -1 means take a minute off the AppDaemon time. This will change when real-time actions happen e.g. triggering a charge or discharge. If your inverter's time is different to the time on the computer running Home Assistant, you may need to skew the time settings made on the inverter when you trigger charging or discharging. Again 1 means the inverter is 1 minute fast and -1 means the inverter is 1 minute slow. Separate start and end options are applied to the start and end time windows, mostly as you want to start battery activity late (not early) and finish early (not late). You can adjust the charge and discharge times written to the inverter by setting the following in apps.yaml : inverter_clock_skew_start , inverter_clock_skew_end - Skews the setting of the charge slot registers vs the predicted start time inverter_clock_skew_discharge_start , inverter_clock_skew_discharge_end - Skews the setting of the discharge slot registers vs the predicted start time battery_scaling - Default value 1.0. This setting is used to scale the battery reported SOC kWh to make it appear bigger or larger than it is e.g. if you have an 80% depth of discharge battery that falsely reports its capacity, set this to 0.8 to report the real figure. If you are going chart your battery SoC in Home Assistant then you may want to use predbat.soc_kw_h0 as your current SoC rather than the usual givtcp_ _soc GivTCP entity so everything lines up import_export_scaling - Default value 1.0. Used to scale the import & export kWh data from GivTCP if the inverter information is incorrect. inverter_battery_rate_min - One per inverter (optional), set in Watts, when set models a \"bug\" in the inverter firmware in some models where if charge or discharge rates are set to 0 you actually get a small amount of charge or discharge. Recommended setting is 200 for Gen 1 hybrids with this issue. inverter_reserve_max - Global, sets the maximum reserve % that maybe set to the inverter, the default is 98 as some Gen 2 inverters and AIO firmware versions refuse to be set to 100. Comment the line out or set to 100 if your inverter allows setting to 100%. battery_charge_power_curve - Some batteries tail off their charge rate at high soc% and this optional configuration item enables you to model this in Predbat. Enter the charging curve as a series of steps of % of max charge rate for each soc percentage. The default is 1.0 (full power) charge all the way to 100%. Example from a GivEnergy 9.5kWh battery with latest firmware and Gen 1 inverter: battery_charge_power_curve: 91 : 0.91 92 : 0.81 93 : 0.71 94 : 0.62 95 : 0.52 96 : 0.43 97 : 0.33 98 : 0.24 99 : 0.24 100 : 0.24","title":"Workarounds"},{"location":"apps-yaml/#triggers","text":"The trigger feature is useful to help trigger your own automations based on Predbat determining that you have spare solar energy or battery that you would otherwise export. For example you may turn an immersion heater or the washing machine on to consume the excess solar power. The triggers count export energy until the next active charge slot only. For each trigger give a name, the minutes of export needed and the energy required in that time. Multiple triggers can be set at once so in total you could use too much energy if all run. Each trigger specified in apps.yaml will create a Home Assistant entity called 'binary_sensor.predbat_export_trigger_ name ' which will be turned on when the condition is valid. Connect this binary sensor to your automation to start whatever you want to trigger. Set the name for each trigger, the number of minutes of solar export you need, and the amount of energy in kWh you will need available during that time period in apps.yaml: For example: export_triggers: - name: \"large\" minutes: 60 energy: 1.0 - name: \"small\" minutes: 15 energy: 0.25 If you wish to trigger based on charging or discharging the battery rather than spare solar energy you can instead use the following binary sensors in Home Assistant: binary_sensor.predbat_charging - Will be True when the home battery is inside a charge slot (either being charged or being held at a level). Note that this does include charge freeze slots where the discharge rate is set to zero without charging the battery. binary_sensor.predbat_discharging - Will be True when the home battery is inside a force discharge slot. This does not include discharge freeze slots where the charge rate is set to zero to export excess solar only.","title":"Triggers"},{"location":"car-charge-planning/","text":"Car charging planning There are two ways to plan car charging slots: If you have Intelligent Octopus import tariff and the Octopus Energy integration - in which case Predbat will use the slots allocated by Octopus Energy in battery prediction Ensure octopus_intelligent_slot in apps.yaml points to the Intelligent Slot sensor in the Octopus Energy integration Set switch.predbat_octopus_intelligent_charging to True Information about the car's battery size will also be extracted from the Octopus Energy integration You will need to set the cars current soc sensor, car_charging_soc in apps.yaml correctly to have accurate results If you set car_charging_limit in apps.yaml then Predbat can also know if the car's limit is set lower than in Intelligent Octopus Let the Octopus app control when your car charges Predbat-led charging - Here Predbat plans the charging based on the upcoming low rate slots Ensure car_charging_limit , car_charging_soc and car_charging_planned are set correctly in apps.yaml Set select.predbat_car_charging_plan_time in Home Assistant to the time you want the car ready by Enable switch.predbat_car_charging_plan_smart if you want to use the cheapest slots only. If you leave this disabled then all low rate slots will be used. This may mean you need to use expert mode and change your low rate threshold to configure which slots should be considered if you have a tariff with more than 2 import rates (e.g. flux) Use an automation based on binary_sensor.predbat_car_charging_slot to control when your car charges NOTE: Multiple cars can be planned with Predbat. See Car charging filtering and Planned car charging in the apps.yaml settings section of the documentation.","title":"Car charging planning"},{"location":"car-charge-planning/#car-charging-planning","text":"There are two ways to plan car charging slots: If you have Intelligent Octopus import tariff and the Octopus Energy integration - in which case Predbat will use the slots allocated by Octopus Energy in battery prediction Ensure octopus_intelligent_slot in apps.yaml points to the Intelligent Slot sensor in the Octopus Energy integration Set switch.predbat_octopus_intelligent_charging to True Information about the car's battery size will also be extracted from the Octopus Energy integration You will need to set the cars current soc sensor, car_charging_soc in apps.yaml correctly to have accurate results If you set car_charging_limit in apps.yaml then Predbat can also know if the car's limit is set lower than in Intelligent Octopus Let the Octopus app control when your car charges Predbat-led charging - Here Predbat plans the charging based on the upcoming low rate slots Ensure car_charging_limit , car_charging_soc and car_charging_planned are set correctly in apps.yaml Set select.predbat_car_charging_plan_time in Home Assistant to the time you want the car ready by Enable switch.predbat_car_charging_plan_smart if you want to use the cheapest slots only. If you leave this disabled then all low rate slots will be used. This may mean you need to use expert mode and change your low rate threshold to configure which slots should be considered if you have a tariff with more than 2 import rates (e.g. flux) Use an automation based on binary_sensor.predbat_car_charging_slot to control when your car charges NOTE: Multiple cars can be planned with Predbat. See Car charging filtering and Planned car charging in the apps.yaml settings section of the documentation.","title":"Car charging planning"},{"location":"configuration-guide/","text":"Configuration guide First get the basics set up, ensure you have the inverter controls configured , you have configured apps.yaml to your setup, and the solar forecast is in place. Make sure your energy rates are configured correctly for import and export. If you have an EV try to set up the car charging sensor correctly so Predbat can tell what part of your historical load is EV charging. You might want to also set to the car charging plan so you can predict when your car is plugged in and how much it will charge. It is recommended that you create a dashboard page with all the required entities to control Predbat. You should try to tune input_number.inverter_loss , input_number.battery_loss and input_number.battery_loss_discharge to the correct % loss for your system in order to get more accurate predictions. Around 4% for each is good for a hybrid inverter. Also set switch.inverter_hybrid to True or False depending upon if you have a Hybrid or AC-Coupled battery. The setting input_number.metric_battery_cycle ( expert mode ) can be used to put a 'virtual cost' in pence on using your battery for charging and discharging. In theory if you think your battery will last say 6000 complete cycles and cost you \u00a34000 and is 9.5kWh then each cycle is 19kWh and so the cost per cycle is \u00a34000 / 19 / 6000 = 3.5p. If you configure this number higher then more expensive plans will be selected which avoids charging and discharging your battery as much. The default is 1p but can be set to 0 if you want to turn this feature off. Note that the cycle cost will not be included in the cost predictions that Predbat produces, its just taken into account in the planning stage. NB: Setting this to a non-zero value will increase your daily cost, but will reduce your home battery usage. input_number.forecast_plan_hours - the number of hours after the next charge slot to include in the plan, default 24 hours is the suggested amount (to match energy rate cycles) switch.set_discharge_during_charge - If turned off disables inverter discharge during charge slots, useful for multi-inverter setups to avoid cross charging when batteries are out of balance. Below is a guide to some of the electricity tariff options and a set of recommended Predbat settings for each tariff type. In theory most tariffs will work out of the box but still it's worth reviewing your settings. Fixed daily rates With a fixed daily rate tariff you will just be predicting the battery levels, no charging or discharging is required although it won't hurt if you leave these options enabled. You should set select.predbat_mode to 'Monitor'. Cheap night rate with bad export rate (e.g. Octopus Go, Economy 7 etc) In this scenario you will want to charge overnight based on the next day's solar forecast and don't want Predbat to force discharge your battery. Recommended settings - these must be changed in Home Assistant once Predbat is running: Item Value Comment select.predbat_mode Control Charge You want Predbat to calculate and control charging input_number.predbat_best_soc_keep 2.0 Tweak this to control what battery level you want to keep as a backup in case you use more energy switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing: Item Value Comment input_number.predbat_forecast_plan_hours 24 If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow switch.predbat_combine_charge_slots True As you have just one overnight rate then one slot is fine input_number.metric_min_improvement 0 Charge less if it's cost neutral You should set select.predbat_mode to 'Control Charge' Cheap night rate, with a good export rate (e.g. Intelligent Octopus with Octopus Outgoing) Follow the instructions from the Cheap Night rate above, but also you will also want to have automatic discharge occurring when the export rates are profitable. Item Value Comment select.predbat_mode Control Charge & Discharge You want Predbat to calculate and control charging and discharging input_number.predbat_best_soc_keep 2.0 Tweak this to control what battery level you want to keep as a backup in case you use more energy switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing, otherwise ignore this: Item Value Comment input_number.predbat_forecast_plan_hours 24 If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow switch.predbat_combine_charge_slots ? Setting to False will allow charging at more expensive day rates when it's worth it to export more input_number.metric_min_improvement 0 Charge less if it's cost neutral input_number.metric_min_improvement_discharge 0.1 Discharge only if there is a profit input_number.metric_battery_cycle ? Higher numbers mean less charging and discharging but higher costs input_number.predbat_best_soc_min ? Can be set non-zero if you want to force a minimum charge level You should set select.predbat_mode to 'Control Charge & Discharge' Multiple rates for import and export (e.g. Octopus Flux & Cozy) Follow the instructions from Cheap Night rate above, but also you will want to have automatic discharge when the export rates are profitable. Recommended settings - these must be changed in Home Assistant once Predbat is running: Item Value Comment select.predbat_mode Control Charge & Discharge You want Predbat to calculate and control charging and discharging input_number.predbat_best_soc_keep 0.5 Use the full battery without going empty switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing, otherwise ignore this: Item Value Comment input_number.predbat_forecast_plan_hours 24 If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow switch.predbat_combine_charge_slots ? Setting to False will allow charging at more expensive day rates when it's worth it to export more input_number.metric_min_improvement 0 Charge less if it's cost neutral input_number.metric_min_improvement_discharge 0.1 Discharge only if there is a profit input_number.metric_battery_cycle ? Higher numbers mean less charging and discharging but higher costs input_number.predbat_best_soc_min 0 Don't use non-zero otherwise all slots will be force charging You should set select.predbat_mode to 'Control Charge & Discharge' Half hourly variable rates (e.g. Octopus Agile) Recommended settings - these must be changed in Home Assistant once Predbat is running: Item Value Comment select.predbat_mode Control Charge & Discharge You want Predbat to calculate and control charging and discharging input_number.predbat_best_soc_keep 0.5 Use the full battery without going empty switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing, otherwise ignore this: Item Value Comment input_number.predbat_forecast_plan_hours 24-48 If you set this to 24 then you will have quicker updates, going to 36/48 for a longer plan input_number.metric_min_improvement 0 Charge less if it's cost neutral input_number.metric_min_improvement_discharge 0.1 Discharge only if there is a profit input_number.metric_battery_cycle ? Higher numbers mean less charging and discharging but higher costs input_number.predbat_best_soc_min 0 Don't use non-zero otherwise all slots will be force charging switch.calculate_fast_plan False The fast plan feature reduces accuracy of planning You should set select.predbat_mode to 'Control Charge & Discharge'","title":"Configuration guide"},{"location":"configuration-guide/#configuration-guide","text":"First get the basics set up, ensure you have the inverter controls configured , you have configured apps.yaml to your setup, and the solar forecast is in place. Make sure your energy rates are configured correctly for import and export. If you have an EV try to set up the car charging sensor correctly so Predbat can tell what part of your historical load is EV charging. You might want to also set to the car charging plan so you can predict when your car is plugged in and how much it will charge. It is recommended that you create a dashboard page with all the required entities to control Predbat. You should try to tune input_number.inverter_loss , input_number.battery_loss and input_number.battery_loss_discharge to the correct % loss for your system in order to get more accurate predictions. Around 4% for each is good for a hybrid inverter. Also set switch.inverter_hybrid to True or False depending upon if you have a Hybrid or AC-Coupled battery. The setting input_number.metric_battery_cycle ( expert mode ) can be used to put a 'virtual cost' in pence on using your battery for charging and discharging. In theory if you think your battery will last say 6000 complete cycles and cost you \u00a34000 and is 9.5kWh then each cycle is 19kWh and so the cost per cycle is \u00a34000 / 19 / 6000 = 3.5p. If you configure this number higher then more expensive plans will be selected which avoids charging and discharging your battery as much. The default is 1p but can be set to 0 if you want to turn this feature off. Note that the cycle cost will not be included in the cost predictions that Predbat produces, its just taken into account in the planning stage. NB: Setting this to a non-zero value will increase your daily cost, but will reduce your home battery usage. input_number.forecast_plan_hours - the number of hours after the next charge slot to include in the plan, default 24 hours is the suggested amount (to match energy rate cycles) switch.set_discharge_during_charge - If turned off disables inverter discharge during charge slots, useful for multi-inverter setups to avoid cross charging when batteries are out of balance. Below is a guide to some of the electricity tariff options and a set of recommended Predbat settings for each tariff type. In theory most tariffs will work out of the box but still it's worth reviewing your settings.","title":"Configuration guide"},{"location":"configuration-guide/#fixed-daily-rates","text":"With a fixed daily rate tariff you will just be predicting the battery levels, no charging or discharging is required although it won't hurt if you leave these options enabled. You should set select.predbat_mode to 'Monitor'.","title":"Fixed daily rates"},{"location":"configuration-guide/#cheap-night-rate-with-bad-export-rate-eg-octopus-go-economy-7-etc","text":"In this scenario you will want to charge overnight based on the next day's solar forecast and don't want Predbat to force discharge your battery. Recommended settings - these must be changed in Home Assistant once Predbat is running: Item Value Comment select.predbat_mode Control Charge You want Predbat to calculate and control charging input_number.predbat_best_soc_keep 2.0 Tweak this to control what battery level you want to keep as a backup in case you use more energy switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing: Item Value Comment input_number.predbat_forecast_plan_hours 24 If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow switch.predbat_combine_charge_slots True As you have just one overnight rate then one slot is fine input_number.metric_min_improvement 0 Charge less if it's cost neutral You should set select.predbat_mode to 'Control Charge'","title":"Cheap night rate with bad export rate (e.g. Octopus Go, Economy 7 etc)"},{"location":"configuration-guide/#cheap-night-rate-with-a-good-export-rate-eg-intelligent-octopus-with-octopus-outgoing","text":"Follow the instructions from the Cheap Night rate above, but also you will also want to have automatic discharge occurring when the export rates are profitable. Item Value Comment select.predbat_mode Control Charge & Discharge You want Predbat to calculate and control charging and discharging input_number.predbat_best_soc_keep 2.0 Tweak this to control what battery level you want to keep as a backup in case you use more energy switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing, otherwise ignore this: Item Value Comment input_number.predbat_forecast_plan_hours 24 If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow switch.predbat_combine_charge_slots ? Setting to False will allow charging at more expensive day rates when it's worth it to export more input_number.metric_min_improvement 0 Charge less if it's cost neutral input_number.metric_min_improvement_discharge 0.1 Discharge only if there is a profit input_number.metric_battery_cycle ? Higher numbers mean less charging and discharging but higher costs input_number.predbat_best_soc_min ? Can be set non-zero if you want to force a minimum charge level You should set select.predbat_mode to 'Control Charge & Discharge'","title":"Cheap night rate, with a good export rate (e.g. Intelligent Octopus with Octopus Outgoing)"},{"location":"configuration-guide/#multiple-rates-for-import-and-export-eg-octopus-flux-cozy","text":"Follow the instructions from Cheap Night rate above, but also you will want to have automatic discharge when the export rates are profitable. Recommended settings - these must be changed in Home Assistant once Predbat is running: Item Value Comment select.predbat_mode Control Charge & Discharge You want Predbat to calculate and control charging and discharging input_number.predbat_best_soc_keep 0.5 Use the full battery without going empty switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing, otherwise ignore this: Item Value Comment input_number.predbat_forecast_plan_hours 24 If you set this to 24 then you will have quicker updates, the cycle repeats itself anyhow switch.predbat_combine_charge_slots ? Setting to False will allow charging at more expensive day rates when it's worth it to export more input_number.metric_min_improvement 0 Charge less if it's cost neutral input_number.metric_min_improvement_discharge 0.1 Discharge only if there is a profit input_number.metric_battery_cycle ? Higher numbers mean less charging and discharging but higher costs input_number.predbat_best_soc_min 0 Don't use non-zero otherwise all slots will be force charging You should set select.predbat_mode to 'Control Charge & Discharge'","title":"Multiple rates for import and export (e.g. Octopus Flux & Cozy)"},{"location":"configuration-guide/#half-hourly-variable-rates-eg-octopus-agile","text":"Recommended settings - these must be changed in Home Assistant once Predbat is running: Item Value Comment select.predbat_mode Control Charge & Discharge You want Predbat to calculate and control charging and discharging input_number.predbat_best_soc_keep 0.5 Use the full battery without going empty switch.predbat_combine_charge_slots True Use one big charge slot If you are using expert mode then these options maybe worth reviewing, otherwise ignore this: Item Value Comment input_number.predbat_forecast_plan_hours 24-48 If you set this to 24 then you will have quicker updates, going to 36/48 for a longer plan input_number.metric_min_improvement 0 Charge less if it's cost neutral input_number.metric_min_improvement_discharge 0.1 Discharge only if there is a profit input_number.metric_battery_cycle ? Higher numbers mean less charging and discharging but higher costs input_number.predbat_best_soc_min 0 Don't use non-zero otherwise all slots will be force charging switch.calculate_fast_plan False The fast plan feature reduces accuracy of planning You should set select.predbat_mode to 'Control Charge & Discharge'","title":"Half hourly variable rates (e.g. Octopus Agile)"},{"location":"creating-charts/","text":"Creating the charts To create the fancy charts: Install Apex Charts https://github.com/RomRider/apexcharts-card There are multiple charts, for each section of the example chart yaml file , create a new apexcharts card and copy the YAML into it. Customise as you like See the video guides for a walkthrough of what the different charts show. Example charts:","title":"Creating the charts"},{"location":"creating-charts/#creating-the-charts","text":"To create the fancy charts: Install Apex Charts https://github.com/RomRider/apexcharts-card There are multiple charts, for each section of the example chart yaml file , create a new apexcharts card and copy the YAML into it. Customise as you like See the video guides for a walkthrough of what the different charts show. Example charts:","title":"Creating the charts"},{"location":"customisation/","text":"Customisation These are the Predbat configuration items in Home Assistant that you can modify to fit your needs, you can configure these in Home Assistant directly. See Displaying output data for information on how to view and edit these entities within Home Assistant. Predbat mode The mode that Predbat operates in will change the operation, this can be configured with select.predbat_mode drop down menu as follows: Monitor Control SOC Only Control charge Control charge & discharge If the switch.predbat_set_read_only is set to True then this prevents Predbat from making modifications to the inverter settings (regardless of the configuration). Predbat will continue making and updating its prediction plan every 5 minutes, but no inverter changes will be made. This is useful if you want to over-ride what predbat is planning to do (e.g. your own automation), or whilst you are learning how Predbat works prior to turning it on 'in anger'. NOTE: Changing the Predbat mode or the read only switch will cause Predbat to reset the inverter settings to default, this will disable both charge and discharge, reset charge and discharge rates to full power and reset the reserve to the default setting Predbat Monitor mode In monitor mode Predbat will not control charging or discharging, inverter balancing will take place if enabled, the plan will show just what is expected based on the current inverter configuration alone. Predbat Control SOC Only mode In Control SOC Only mode Predbat will adjust the target charge percentage (SOC target) according to the Best plan, but the charge window will not be modified. This can be useful if you just have one fixed charge slot per day and you only want Predbat to control the percentage. CAUTION: If the charge window is disabled then no charging will take place. Predbat Control Charge mode In Control Charge mode Predbat will set the charge times and charge percentages according to the Best plan, charging can be enabled and disabled by Predbat. Predbat Control Charge & Discharge mode In Control Charge and Discharge mode Predbat will set both charge and discharge times and control charge and discharge percentages. If you have set the switch.predbat_set_discharge_freeze_only to True then forced export won't occur but Predbat can force the export of solar power to the grid when desired. Expert mode Predbat has a toggle switch called switch.predbat_expert_mode which is off by default for new installs (on by default for upgraded installs). A lot of configuration items will not be available unless expert mode is enabled. It's recommended for new users to start without expert mode and then maybe enable it later once you become more confident with the tool. Performance related By default Predbat controls the inverter and updates the plan every 5 minutes, this can however use a lot of CPU power especially on more complex tariffs like Agile when run on lower power machines such as Raspberry PIs and some thin clients. You can tweak input_number.predbat_calculate_plan_every ( expert mode ) to reduce the frequency of replanning while keeping the inverter control in the 5 minute slots. E.g. a value of 10 or 15 minutes should also give good results. If you have performance problems leave switch.predbat_calculate_second_pass ( expert mode ) turned Off as it's quite CPU intensive and provides very little improvement for most systems. If you have performance problems turn switch.predbat_calculate_fast_plan ( expert mode ) On to help reduce your CPU load. Battery loss options input_number.battery_loss accounts for energy lost charging the battery, default 0.05 is 5% input_number.battery_loss_discharge accounts for energy lost discharging the battery, default 0.05 is 5% input_number.inverter_loss accounts for energy loss during going from DC to AC or AC to DC, default is 0% for legacy reasons but please adjust. switch.inverter_hybrid When True you have a hybrid inverter so no inverter losses for DC charging. When false you have inverter losses as it's AC coupled battery. input_number.metric_battery_cycle ( expert mode ) Sets the cost in pence per kWh of using your battery for charging and discharging. Higher numbers will reduce battery cycles at the expense of using higher energy costs. Figures of around 1p-5p are recommended, the default is 1p per kWh. input_number.predbat_metric_battery_value_scaling ( expert mode ) Can be used to scale the value of the energy in the battery at the end of the plan. The battery value is accounted for in the optimisations at the lowest future import rate including charging and inverter losses. A value of 1.0 means no change to this, while lower than 1.0 means to value future battery levels less, greater than 1.0 will value it more (and hence hold more charge at the end of the plan). Scaling and weight options input_number.battery_rate_max_scaling adjusts your maximum charge/discharge rate from that reported by GivTCP e.g. a value of 1.1 would simulate a 10% faster charge/discharge than reported by the inverter switch.predbat_battery_capacity_nominal - When enabled Predbat uses the reported battery size from the Nominal field rather than from the normal GivTCP reported size. If your battery size is reported wrongly maybe try turning this on and see if it helps. input_number.load_scaling is a Scaling factor applied to historical load, tune up if you want to be more pessimistic on future consumption Use 1.0 to use exactly previous load data (1.1 would add 10% to load) input_number.load_scaling10 is a Scaling factor applied to historical load only for the PV10% scenario (this is in addition to load_scaling). This can be used to make the 10% scenario take into account extra load usage and hence be more pessimistic while leaving the central scenario unchanged. The default is 1.1 meaning an extra 10% load is added. This will only have an impact if the PV 10% weighting is non-zero. input_number.pv_scaling is a scaling factor applied to PV data, tune down if you want to be more pessimistic on PV production vs Solcast Use 1.0 to use exactly the Solcast data (0.9 would remove 10% from forecast) input_number.pv_metric10_weight is the weighting given to the 10% PV scenario. Use 0.0 to disable this. A value of 0.1 assumes that 1:10 times we get the 10% scenario and hence to count this in the metric benefit/cost. A value of 0.15 is recommended. Historical load data The historical load data is taken from the load sensor as configured in apps.yaml and the days are selected using days_previous and weighted using *days_previous_weight in the same configuration file switch.predbat_load_filter_modal ( expert mode ) when enabled will automatically discard the lowest daily consumption day from the list of days to use (provided you have more than 1 day selected in days_previous). This can be used to ignore a single low usage day in your average calculation. By default is feature is enabled but can be disabled only in expert mode. Car Charging Car charging hold options Car charging hold is a feature where you try to filter out previous car charging from your historical data so that future predictions are more accurate. When car_charging_hold is enabled loads of above the power threshold car_charging_threshold then you are assumed to be charging the car and car_charging_rate will be subtracted from the historical load data. For more accurate results can you use an incrementing energy sensor set with car_charging_energy in the apps.yml then historical data will be subtracted from the load data instead. car_charging_energy_scale Is used to scale the car_charging_energy sensor, the default units are kWh so if you had a sensor in watts you might use 0.001 instead. input_number.car_charging_rate - Set to the car's charging rate in kW per hour (normally 7.5 for 7.5kWh), but will be pulled automatically from Octopus Energy integration if enabled for Octopus Intelligent. car_charging_loss gives the amount of energy lost when charging the car (load in the home vs energy added to the battery). A good setting is 0.08 which is 8%. Car charging plan options Car charging planning - is only used if Intelligent Octopus isn't enabled and car_charging_planned is connected correctly. This feature allows Predbat to create a plan for when you car will charge, but you will have to create an automation to trigger your car to charge using binary_sensor.predbat_car_charging_slot if you want it to match the plan. car_charging_plan_time - When using Predbat-led planning set this to the time you want the car to be charged by car_charging_plan_smart - When enabled (True) allows Predbat to allocate car charging slots to the cheapest times, when disabled (False) all low rate slots will be used in time order. switch.predbat_octopus_intelligent_charging when true enables the Intelligent Octopus charging feature which will make Predbat create a car charging plan which is taken from the Intelligent Octopus plan you must have set octopus_intelligent_slot sensor in apps.yaml to enable this feature. If Octopus Intelligent Charging is enabled the switch switch.predbat_octopus_intelligent_ignore_unplugged ( expert mode ) can be used to prevent Predbat from assuming the car will be charging when the car is unplugged. This will only work correctly if car_charging_planned is set correctly in apps.yaml to detect your car being plugged in. Control how your battery behaves during car charging: car_charging_from_battery - When True the car can drain the home battery, Predbat will manage the correct level of battery accordingly. When False home battery discharge will be prevented when your car charges, all load from the car and home will be from the grid. This is achieved by setting the discharge rate to 0 during car charging and to the maximum otherwise, hence if you turn this switch Off you won't be able to change your discharge rate outside Predbat. The home battery can still charge from the grid/solar in either case. Only use this if Predbat knows your car charging plan, e.g. you are using Intelligent Octopus or you use the car slots in Predbat to control your car charging. If your car does not have an SOC sensor and you are not using Octopus Intelligent you can set switch.predbat_car_charging_manual_soc to have Predbat create input_number.predbat_car_charging_manual_soc_kwh which will hold the cars current state of charge (soc) in kWh. You will need to manually set this to the cars current charge level before charging, Predbat will increment it during charging sessions but will not reset it automatically. Calculation options See the Predbat mode setting as above for basic calculation options switch.predbat_calculate_regions ( expert mode ) When True the a second pass of the initial thresholds is calculated in 4 hour regions before forming the detailed plan. Is True by default but can be turned off in expert mode. switch.predbat_calculate_fast_plan ( expert mode ) When True the plan is calculated with a limited number of windows to make calculations faster. When False (default) all windows are considered but planning will take a little longer but be more accurate. The end result is unlikely to change in fast mode as the next 8 windows are always considered in the plan, but the longer term plan will be less accurate. switch.predbat_calculate_discharge_oncharge ( expert mode ) When True calculated discharge slots will disable or move charge slots, allowing them to intermix. When False discharge slots will never be placed into charge slots. switch.predbat_calculate_tweak_plan ( expert mode ) When True causes Predbat to perform a second pass optimisation across the next 8 charge and discharge windows in time order. This can help to slightly improve the plan for tariffs like Agile but can make it worse in some fixed rate tariffs which you want to discharge late. switch.predbat_calculate_second_pass ( expert mode ) When True causes Predbat to perform a second pass optimisation across all the charge and discharge windows in time order. NOTE: This feature is quite slow and so may need a higher performance machine This can help to slightly improve the plan for tariffs like Agile but can make it worse in some fixed rate tariffs which you want to discharge late. Battery margins and metrics options input_number.best_soc_keep is the minimum battery level in kWh that Predbat will to try to keep above during the whole period of the simulation time. This is a soft constraint only so it is possible for your SoC to drop below this - use input_number.best_soc_min for hard SoC constraint that will always be maintained. It's usually good to have best_soc_keep set to a value above 0 to allow some margin in case you use more energy than planned between charge slots. input_number.best_soc_min ( expert mode ) sets the minimum charge level (in kWh) for charging during each slot and the minimum discharge level also (set to 0 if you want to skip some slots). If you set this to a non-zero value you will need to use the low rate threshold to control which slots you charge from or you may charge all the time. input_number.best_soc_max ( expert mode ) sets the maximum charge level (in kWh) for charging during each slot. A value of 0 disables this feature. switch.combine_charge_slots Controls if charge slots of > 30 minutes can be combined. When disabled they will be split up, increasing run times but potentially more accurate for planning. Turn this off if you want to enable ad-hoc import during long periods of higher rates but you wouldn't charge normally in that period (e.g. pre-charge at day rate before a saving session). The default is enable (True) switch.combine_discharge_slots ( expert mode ) Controls if discharge slots of > 30 minute can be combined. When disabled they will be split up, increasing run times but potentially more accurate for planning. The default is disabled (False) input_number.metric_min_improvement ( expert mode ) sets the minimum cost improvement that it's worth lowering the battery SOC % for. If it's 0 then this is disabled and the battery will be charged less if it's cost neutral. If you use pv_metric10_weight then you probably don't need to enable this as the 10% forecast does the same thing better Do not use if you have multiple charge windows in a given period as it won't lead to good results (e.g. Agile) You could even go to something like -0.1 to say you would charge less even if it cost up to 0.1p more (best used with metric10) input_number.metric_min_improvement_discharge ( expert mode ) Sets the minimum pence cost improvement it's worth doing a forced discharge (and export) for. A value of 0.1 is the default which prevents any marginal discharges. If you increase this value (e.g. you only want to discharge/forced export if definitely very profitable), then discharges will become less common and shorter. input_number.rate_low_threshold ( expert mode ) When 0 (default) this is automatic but can be overridden. When non zero it sets the threshold below average rates as the minimum to consider for a charge window, 0.8 = 80% of average rate If you set this too low you might not get enough charge slots. If it's too high you might get too many in the 24-hour period which makes optimisation harder. input_number.rate_high_threshold ( expert mode ) When 0 (default) this is automatic but can be overridden. When non zero it sets the threshold above average rates as to the minimum export rate to consider exporting for - 1.2 = 20% above average rate If you set this too high you might not get any export slots. If it's too low you might get too many in the 24-hour period. input_number.metric_future_rate_offset_import ( expert mode ) Sets an offset to apply to future import energy rates that are not yet published, best used for variable rate tariffs such as Agile import where the rates are not published until 4pm. If you set this to a positive value then Predbat will assume unpublished import rates are higher by the given amount. input_number.metric_future_rate_offset_export ( expert mode ) Sets an offset to apply to future export energy rates that are not yet published, best used for variable rate tariffs such as Agile export where the rates are not published until 4pm. If you set this to a negative value then Predbat will assume unpublished export rates are lower by the given amount. switch.predbat_calculate_inday_adjustment ( expert mode ) Enabled by default with damping of 0.95. When enabled will calculate the difference between today's actual load and today's predicated load and adjust the rest of the days usage prediction accordingly. A scale factor can be set with input_number.predbat_metric_inday_adjust_damping ( expert mode ) to either scale up or down the impact of the in-day adjustment (lower numbers scale down its impact). The in-day adjustment factor can be see in predbat.load_inday_adjustment and charted with the In Day Adjustment chart (template can be found in the charts template in Github). Inverter control options switch.set_status_notify Enables mobile notification about changes to the Predbat state (e.g. Charge, Discharge etc). On by default. switch.set_inverter_notify Enables mobile notification about all changes to inverter registers (e.g. setting window, turning discharge on/off). Off by default. switch.predbat_set_charge_low_power Enables low power charging mode where the max charge rate will be limited to the lowest possible to meet the charge target. Only really effective for charge windows >30 minutes. Off by default. switch.set_reserve_enable ( expert_mode ) When enabled the reserve setting is used to hold the battery charge level once it has been reached or to protect against discharging beyond the set limit. Enabled by default. switch.set_charge_freeze ( expert mode ) When enabled will allow Predbat to hold the current battery level while drawing from the grid/solar as an alternative to charging. Enabled by default. switch.set_discharge_freeze_only ( expert mode ) When enabled forced discharge is prevented, but discharge freeze can be used (if enabled) to export excess solar rather than charging the battery. This is useful with tariffs that pay you for solar exports but don't allow forced export (brown energy). If you have switch.inverter_hybrid set to False then if switch.inverter_soc_reset ( expert mode ) is set to True then the target SOC % will be reset to 100% outside a charge window. This may be required for AIO inverter to ensure it charges from solar. input_number.set_reserve_min Defines the reserve percentage to reset the reserve to when not in use, a value of 4 is the minimum and recommended to make use of the full battery switch.inverter_soc_reset ( expert mode ) When enabled the target SOC for the inverter(s) will be reset to 100% when a charge slot is not active, this can be used to workaround some firmware issues where the SOC target is used for solar charging as well as grid charging. When disabled the SOC % will not be changed after a charge slot. This is disabled by default. Balance Inverters When you have two or more inverters it's possible they get out of sync so they are at different charge levels or they start to cross-charge (one discharges into another). When enabled, balance inverters tries to recover this situation by disabling either charging or discharging from one of the batteries until they re-align. The apps.yaml contains a setting balance_inverters_seconds which defines how often to run the balancing, 30 seconds is recommended if your machine is fast enough, but the default is 60 seconds. Enable the switch.predbat_balance_inverters_enable switch in Home Assistant to enable this feature. switch.predbat_balance_inverters_charge - Is used to toggle on/off balancing while the batteries are charging switch.predbat_balance_inverters_discharge - Is used to toggle on/off balancing while the batteries are discharging switch.predbat_balance_inverters_crosscharge - Is used to toggle on/off balancing when the batteries are cross charging input_number.predbat_balance_inverters_threshold_charge - Sets the minimum percentage divergence of SOC during charge before balancing, default is 1% input_number.predbat_balance_inverters_threshold_discharge - Sets the minimum percentage divergence of SOC during discharge before balancing, default is 1% iBoost model options iBoost model, when enabled with switch.iboost_enable tries to model excess solar energy being used to heat hot water (or similar). The predicted output from the iBoost model is returned in iboost_best . The following entities are only available when you turn on iboost enable: iboost_solar When enabled assumes iBoost will use solar power to boost. iboost_min_soc sets the minimum home battery soc % to enable iboost solar on, default 0 iboost_gas When enabled assumes IBoost will operate when electric rates are lower than gas rates. Note: Gas rates have to be configured in apps.yaml with metric_octopus_gas iboost_gas_scale Sets the scaling of the gas rates used before comparing with electric rates, to account for losses iboost_charging Assume IBoost operates when the battery is charging (can be combined with iboost_gas or not) iboost_max_energy Sets the max energy sets the number of kwh that iBoost can consume during a day before turning off - default 3kWh iboost_max_power Sets the maximum power in watts to consume - default 2400 iboost_min_power Sets the minimum power in watts to consume - default 500 You will see predbat.iboost_today entity which tracks the estimated amount consumed during the day, and resets at night The binary_sensor.iboost_active entity will be enabled when IBoost should be active, can be used for automations to trigger boost If you have an incrementing Sensor that tracks iBoost energy usage then you should set iboost_energy_today sensor in apps.yaml to point to it and optionally set iboost_energy_scaling if the sensor isn't in kWh. Holiday mode When you go away you are likely to use less electricity and so the previous load data will be quite pessimistic. Using the Home Assistant entity input_number.predbat_holiday_days_left you can set the number of full days that you will be away for (including today). The number will count down by 1 day at midnight until it gets back to zero. Whilst holiday days left is non-zero, Predbat's 'holiday mode' is active. When Predbat's 'holiday mode' is active the historical load data will be taken from yesterday's data (1 day ago) rather than from the days_previous setting in apps.yaml. This means Predbat will adjust more quickly to the new usage pattern. If you have been away for a longer period of time (more than your normal days_previous setting) then obviously it's going to take longer for the historical data to catch up, you could then enable holiday mode for another 7 days after your return. In summary: For short holidays set holiday_days_left to the number of full days you are away, including today but excluding the return day For longer holidays set holiday_days_left to the number of days you are away plus another 7 days until the data catches back up Debug debug_enable when on prints lots of debug, leave off by default plan_debug ( expert mode ) when enabled adds some extra debug to the Predbat HTML plan","title":"Customisation"},{"location":"customisation/#customisation","text":"These are the Predbat configuration items in Home Assistant that you can modify to fit your needs, you can configure these in Home Assistant directly. See Displaying output data for information on how to view and edit these entities within Home Assistant.","title":"Customisation"},{"location":"customisation/#predbat-mode","text":"The mode that Predbat operates in will change the operation, this can be configured with select.predbat_mode drop down menu as follows: Monitor Control SOC Only Control charge Control charge & discharge If the switch.predbat_set_read_only is set to True then this prevents Predbat from making modifications to the inverter settings (regardless of the configuration). Predbat will continue making and updating its prediction plan every 5 minutes, but no inverter changes will be made. This is useful if you want to over-ride what predbat is planning to do (e.g. your own automation), or whilst you are learning how Predbat works prior to turning it on 'in anger'. NOTE: Changing the Predbat mode or the read only switch will cause Predbat to reset the inverter settings to default, this will disable both charge and discharge, reset charge and discharge rates to full power and reset the reserve to the default setting","title":"Predbat mode"},{"location":"customisation/#predbat-monitor-mode","text":"In monitor mode Predbat will not control charging or discharging, inverter balancing will take place if enabled, the plan will show just what is expected based on the current inverter configuration alone.","title":"Predbat Monitor mode"},{"location":"customisation/#predbat-control-soc-only-mode","text":"In Control SOC Only mode Predbat will adjust the target charge percentage (SOC target) according to the Best plan, but the charge window will not be modified. This can be useful if you just have one fixed charge slot per day and you only want Predbat to control the percentage. CAUTION: If the charge window is disabled then no charging will take place.","title":"Predbat Control SOC Only mode"},{"location":"customisation/#predbat-control-charge-mode","text":"In Control Charge mode Predbat will set the charge times and charge percentages according to the Best plan, charging can be enabled and disabled by Predbat.","title":"Predbat Control Charge mode"},{"location":"customisation/#predbat-control-charge-discharge-mode","text":"In Control Charge and Discharge mode Predbat will set both charge and discharge times and control charge and discharge percentages. If you have set the switch.predbat_set_discharge_freeze_only to True then forced export won't occur but Predbat can force the export of solar power to the grid when desired.","title":"Predbat Control Charge & Discharge mode"},{"location":"customisation/#expert-mode","text":"Predbat has a toggle switch called switch.predbat_expert_mode which is off by default for new installs (on by default for upgraded installs). A lot of configuration items will not be available unless expert mode is enabled. It's recommended for new users to start without expert mode and then maybe enable it later once you become more confident with the tool.","title":"Expert mode"},{"location":"customisation/#performance-related","text":"By default Predbat controls the inverter and updates the plan every 5 minutes, this can however use a lot of CPU power especially on more complex tariffs like Agile when run on lower power machines such as Raspberry PIs and some thin clients. You can tweak input_number.predbat_calculate_plan_every ( expert mode ) to reduce the frequency of replanning while keeping the inverter control in the 5 minute slots. E.g. a value of 10 or 15 minutes should also give good results. If you have performance problems leave switch.predbat_calculate_second_pass ( expert mode ) turned Off as it's quite CPU intensive and provides very little improvement for most systems. If you have performance problems turn switch.predbat_calculate_fast_plan ( expert mode ) On to help reduce your CPU load.","title":"Performance related"},{"location":"customisation/#battery-loss-options","text":"input_number.battery_loss accounts for energy lost charging the battery, default 0.05 is 5% input_number.battery_loss_discharge accounts for energy lost discharging the battery, default 0.05 is 5% input_number.inverter_loss accounts for energy loss during going from DC to AC or AC to DC, default is 0% for legacy reasons but please adjust. switch.inverter_hybrid When True you have a hybrid inverter so no inverter losses for DC charging. When false you have inverter losses as it's AC coupled battery. input_number.metric_battery_cycle ( expert mode ) Sets the cost in pence per kWh of using your battery for charging and discharging. Higher numbers will reduce battery cycles at the expense of using higher energy costs. Figures of around 1p-5p are recommended, the default is 1p per kWh. input_number.predbat_metric_battery_value_scaling ( expert mode ) Can be used to scale the value of the energy in the battery at the end of the plan. The battery value is accounted for in the optimisations at the lowest future import rate including charging and inverter losses. A value of 1.0 means no change to this, while lower than 1.0 means to value future battery levels less, greater than 1.0 will value it more (and hence hold more charge at the end of the plan).","title":"Battery loss options"},{"location":"customisation/#scaling-and-weight-options","text":"input_number.battery_rate_max_scaling adjusts your maximum charge/discharge rate from that reported by GivTCP e.g. a value of 1.1 would simulate a 10% faster charge/discharge than reported by the inverter switch.predbat_battery_capacity_nominal - When enabled Predbat uses the reported battery size from the Nominal field rather than from the normal GivTCP reported size. If your battery size is reported wrongly maybe try turning this on and see if it helps. input_number.load_scaling is a Scaling factor applied to historical load, tune up if you want to be more pessimistic on future consumption Use 1.0 to use exactly previous load data (1.1 would add 10% to load) input_number.load_scaling10 is a Scaling factor applied to historical load only for the PV10% scenario (this is in addition to load_scaling). This can be used to make the 10% scenario take into account extra load usage and hence be more pessimistic while leaving the central scenario unchanged. The default is 1.1 meaning an extra 10% load is added. This will only have an impact if the PV 10% weighting is non-zero. input_number.pv_scaling is a scaling factor applied to PV data, tune down if you want to be more pessimistic on PV production vs Solcast Use 1.0 to use exactly the Solcast data (0.9 would remove 10% from forecast) input_number.pv_metric10_weight is the weighting given to the 10% PV scenario. Use 0.0 to disable this. A value of 0.1 assumes that 1:10 times we get the 10% scenario and hence to count this in the metric benefit/cost. A value of 0.15 is recommended.","title":"Scaling and weight options"},{"location":"customisation/#historical-load-data","text":"The historical load data is taken from the load sensor as configured in apps.yaml and the days are selected using days_previous and weighted using *days_previous_weight in the same configuration file switch.predbat_load_filter_modal ( expert mode ) when enabled will automatically discard the lowest daily consumption day from the list of days to use (provided you have more than 1 day selected in days_previous). This can be used to ignore a single low usage day in your average calculation. By default is feature is enabled but can be disabled only in expert mode.","title":"Historical load data"},{"location":"customisation/#car-charging","text":"","title":"Car Charging"},{"location":"customisation/#car-charging-hold-options","text":"Car charging hold is a feature where you try to filter out previous car charging from your historical data so that future predictions are more accurate. When car_charging_hold is enabled loads of above the power threshold car_charging_threshold then you are assumed to be charging the car and car_charging_rate will be subtracted from the historical load data. For more accurate results can you use an incrementing energy sensor set with car_charging_energy in the apps.yml then historical data will be subtracted from the load data instead. car_charging_energy_scale Is used to scale the car_charging_energy sensor, the default units are kWh so if you had a sensor in watts you might use 0.001 instead. input_number.car_charging_rate - Set to the car's charging rate in kW per hour (normally 7.5 for 7.5kWh), but will be pulled automatically from Octopus Energy integration if enabled for Octopus Intelligent. car_charging_loss gives the amount of energy lost when charging the car (load in the home vs energy added to the battery). A good setting is 0.08 which is 8%.","title":"Car charging hold options"},{"location":"customisation/#car-charging-plan-options","text":"Car charging planning - is only used if Intelligent Octopus isn't enabled and car_charging_planned is connected correctly. This feature allows Predbat to create a plan for when you car will charge, but you will have to create an automation to trigger your car to charge using binary_sensor.predbat_car_charging_slot if you want it to match the plan. car_charging_plan_time - When using Predbat-led planning set this to the time you want the car to be charged by car_charging_plan_smart - When enabled (True) allows Predbat to allocate car charging slots to the cheapest times, when disabled (False) all low rate slots will be used in time order. switch.predbat_octopus_intelligent_charging when true enables the Intelligent Octopus charging feature which will make Predbat create a car charging plan which is taken from the Intelligent Octopus plan you must have set octopus_intelligent_slot sensor in apps.yaml to enable this feature. If Octopus Intelligent Charging is enabled the switch switch.predbat_octopus_intelligent_ignore_unplugged ( expert mode ) can be used to prevent Predbat from assuming the car will be charging when the car is unplugged. This will only work correctly if car_charging_planned is set correctly in apps.yaml to detect your car being plugged in. Control how your battery behaves during car charging: car_charging_from_battery - When True the car can drain the home battery, Predbat will manage the correct level of battery accordingly. When False home battery discharge will be prevented when your car charges, all load from the car and home will be from the grid. This is achieved by setting the discharge rate to 0 during car charging and to the maximum otherwise, hence if you turn this switch Off you won't be able to change your discharge rate outside Predbat. The home battery can still charge from the grid/solar in either case. Only use this if Predbat knows your car charging plan, e.g. you are using Intelligent Octopus or you use the car slots in Predbat to control your car charging. If your car does not have an SOC sensor and you are not using Octopus Intelligent you can set switch.predbat_car_charging_manual_soc to have Predbat create input_number.predbat_car_charging_manual_soc_kwh which will hold the cars current state of charge (soc) in kWh. You will need to manually set this to the cars current charge level before charging, Predbat will increment it during charging sessions but will not reset it automatically.","title":"Car charging plan options"},{"location":"customisation/#calculation-options","text":"See the Predbat mode setting as above for basic calculation options switch.predbat_calculate_regions ( expert mode ) When True the a second pass of the initial thresholds is calculated in 4 hour regions before forming the detailed plan. Is True by default but can be turned off in expert mode. switch.predbat_calculate_fast_plan ( expert mode ) When True the plan is calculated with a limited number of windows to make calculations faster. When False (default) all windows are considered but planning will take a little longer but be more accurate. The end result is unlikely to change in fast mode as the next 8 windows are always considered in the plan, but the longer term plan will be less accurate. switch.predbat_calculate_discharge_oncharge ( expert mode ) When True calculated discharge slots will disable or move charge slots, allowing them to intermix. When False discharge slots will never be placed into charge slots. switch.predbat_calculate_tweak_plan ( expert mode ) When True causes Predbat to perform a second pass optimisation across the next 8 charge and discharge windows in time order. This can help to slightly improve the plan for tariffs like Agile but can make it worse in some fixed rate tariffs which you want to discharge late. switch.predbat_calculate_second_pass ( expert mode ) When True causes Predbat to perform a second pass optimisation across all the charge and discharge windows in time order. NOTE: This feature is quite slow and so may need a higher performance machine This can help to slightly improve the plan for tariffs like Agile but can make it worse in some fixed rate tariffs which you want to discharge late.","title":"Calculation options"},{"location":"customisation/#battery-margins-and-metrics-options","text":"input_number.best_soc_keep is the minimum battery level in kWh that Predbat will to try to keep above during the whole period of the simulation time. This is a soft constraint only so it is possible for your SoC to drop below this - use input_number.best_soc_min for hard SoC constraint that will always be maintained. It's usually good to have best_soc_keep set to a value above 0 to allow some margin in case you use more energy than planned between charge slots. input_number.best_soc_min ( expert mode ) sets the minimum charge level (in kWh) for charging during each slot and the minimum discharge level also (set to 0 if you want to skip some slots). If you set this to a non-zero value you will need to use the low rate threshold to control which slots you charge from or you may charge all the time. input_number.best_soc_max ( expert mode ) sets the maximum charge level (in kWh) for charging during each slot. A value of 0 disables this feature. switch.combine_charge_slots Controls if charge slots of > 30 minutes can be combined. When disabled they will be split up, increasing run times but potentially more accurate for planning. Turn this off if you want to enable ad-hoc import during long periods of higher rates but you wouldn't charge normally in that period (e.g. pre-charge at day rate before a saving session). The default is enable (True) switch.combine_discharge_slots ( expert mode ) Controls if discharge slots of > 30 minute can be combined. When disabled they will be split up, increasing run times but potentially more accurate for planning. The default is disabled (False) input_number.metric_min_improvement ( expert mode ) sets the minimum cost improvement that it's worth lowering the battery SOC % for. If it's 0 then this is disabled and the battery will be charged less if it's cost neutral. If you use pv_metric10_weight then you probably don't need to enable this as the 10% forecast does the same thing better Do not use if you have multiple charge windows in a given period as it won't lead to good results (e.g. Agile) You could even go to something like -0.1 to say you would charge less even if it cost up to 0.1p more (best used with metric10) input_number.metric_min_improvement_discharge ( expert mode ) Sets the minimum pence cost improvement it's worth doing a forced discharge (and export) for. A value of 0.1 is the default which prevents any marginal discharges. If you increase this value (e.g. you only want to discharge/forced export if definitely very profitable), then discharges will become less common and shorter. input_number.rate_low_threshold ( expert mode ) When 0 (default) this is automatic but can be overridden. When non zero it sets the threshold below average rates as the minimum to consider for a charge window, 0.8 = 80% of average rate If you set this too low you might not get enough charge slots. If it's too high you might get too many in the 24-hour period which makes optimisation harder. input_number.rate_high_threshold ( expert mode ) When 0 (default) this is automatic but can be overridden. When non zero it sets the threshold above average rates as to the minimum export rate to consider exporting for - 1.2 = 20% above average rate If you set this too high you might not get any export slots. If it's too low you might get too many in the 24-hour period. input_number.metric_future_rate_offset_import ( expert mode ) Sets an offset to apply to future import energy rates that are not yet published, best used for variable rate tariffs such as Agile import where the rates are not published until 4pm. If you set this to a positive value then Predbat will assume unpublished import rates are higher by the given amount. input_number.metric_future_rate_offset_export ( expert mode ) Sets an offset to apply to future export energy rates that are not yet published, best used for variable rate tariffs such as Agile export where the rates are not published until 4pm. If you set this to a negative value then Predbat will assume unpublished export rates are lower by the given amount. switch.predbat_calculate_inday_adjustment ( expert mode ) Enabled by default with damping of 0.95. When enabled will calculate the difference between today's actual load and today's predicated load and adjust the rest of the days usage prediction accordingly. A scale factor can be set with input_number.predbat_metric_inday_adjust_damping ( expert mode ) to either scale up or down the impact of the in-day adjustment (lower numbers scale down its impact). The in-day adjustment factor can be see in predbat.load_inday_adjustment and charted with the In Day Adjustment chart (template can be found in the charts template in Github).","title":"Battery margins and metrics options"},{"location":"customisation/#inverter-control-options","text":"switch.set_status_notify Enables mobile notification about changes to the Predbat state (e.g. Charge, Discharge etc). On by default. switch.set_inverter_notify Enables mobile notification about all changes to inverter registers (e.g. setting window, turning discharge on/off). Off by default. switch.predbat_set_charge_low_power Enables low power charging mode where the max charge rate will be limited to the lowest possible to meet the charge target. Only really effective for charge windows >30 minutes. Off by default. switch.set_reserve_enable ( expert_mode ) When enabled the reserve setting is used to hold the battery charge level once it has been reached or to protect against discharging beyond the set limit. Enabled by default. switch.set_charge_freeze ( expert mode ) When enabled will allow Predbat to hold the current battery level while drawing from the grid/solar as an alternative to charging. Enabled by default. switch.set_discharge_freeze_only ( expert mode ) When enabled forced discharge is prevented, but discharge freeze can be used (if enabled) to export excess solar rather than charging the battery. This is useful with tariffs that pay you for solar exports but don't allow forced export (brown energy). If you have switch.inverter_hybrid set to False then if switch.inverter_soc_reset ( expert mode ) is set to True then the target SOC % will be reset to 100% outside a charge window. This may be required for AIO inverter to ensure it charges from solar. input_number.set_reserve_min Defines the reserve percentage to reset the reserve to when not in use, a value of 4 is the minimum and recommended to make use of the full battery switch.inverter_soc_reset ( expert mode ) When enabled the target SOC for the inverter(s) will be reset to 100% when a charge slot is not active, this can be used to workaround some firmware issues where the SOC target is used for solar charging as well as grid charging. When disabled the SOC % will not be changed after a charge slot. This is disabled by default.","title":"Inverter control options"},{"location":"customisation/#balance-inverters","text":"When you have two or more inverters it's possible they get out of sync so they are at different charge levels or they start to cross-charge (one discharges into another). When enabled, balance inverters tries to recover this situation by disabling either charging or discharging from one of the batteries until they re-align. The apps.yaml contains a setting balance_inverters_seconds which defines how often to run the balancing, 30 seconds is recommended if your machine is fast enough, but the default is 60 seconds. Enable the switch.predbat_balance_inverters_enable switch in Home Assistant to enable this feature. switch.predbat_balance_inverters_charge - Is used to toggle on/off balancing while the batteries are charging switch.predbat_balance_inverters_discharge - Is used to toggle on/off balancing while the batteries are discharging switch.predbat_balance_inverters_crosscharge - Is used to toggle on/off balancing when the batteries are cross charging input_number.predbat_balance_inverters_threshold_charge - Sets the minimum percentage divergence of SOC during charge before balancing, default is 1% input_number.predbat_balance_inverters_threshold_discharge - Sets the minimum percentage divergence of SOC during discharge before balancing, default is 1%","title":"Balance Inverters"},{"location":"customisation/#iboost-model-options","text":"iBoost model, when enabled with switch.iboost_enable tries to model excess solar energy being used to heat hot water (or similar). The predicted output from the iBoost model is returned in iboost_best . The following entities are only available when you turn on iboost enable: iboost_solar When enabled assumes iBoost will use solar power to boost. iboost_min_soc sets the minimum home battery soc % to enable iboost solar on, default 0 iboost_gas When enabled assumes IBoost will operate when electric rates are lower than gas rates. Note: Gas rates have to be configured in apps.yaml with metric_octopus_gas iboost_gas_scale Sets the scaling of the gas rates used before comparing with electric rates, to account for losses iboost_charging Assume IBoost operates when the battery is charging (can be combined with iboost_gas or not) iboost_max_energy Sets the max energy sets the number of kwh that iBoost can consume during a day before turning off - default 3kWh iboost_max_power Sets the maximum power in watts to consume - default 2400 iboost_min_power Sets the minimum power in watts to consume - default 500 You will see predbat.iboost_today entity which tracks the estimated amount consumed during the day, and resets at night The binary_sensor.iboost_active entity will be enabled when IBoost should be active, can be used for automations to trigger boost If you have an incrementing Sensor that tracks iBoost energy usage then you should set iboost_energy_today sensor in apps.yaml to point to it and optionally set iboost_energy_scaling if the sensor isn't in kWh.","title":"iBoost model options"},{"location":"customisation/#holiday-mode","text":"When you go away you are likely to use less electricity and so the previous load data will be quite pessimistic. Using the Home Assistant entity input_number.predbat_holiday_days_left you can set the number of full days that you will be away for (including today). The number will count down by 1 day at midnight until it gets back to zero. Whilst holiday days left is non-zero, Predbat's 'holiday mode' is active. When Predbat's 'holiday mode' is active the historical load data will be taken from yesterday's data (1 day ago) rather than from the days_previous setting in apps.yaml. This means Predbat will adjust more quickly to the new usage pattern. If you have been away for a longer period of time (more than your normal days_previous setting) then obviously it's going to take longer for the historical data to catch up, you could then enable holiday mode for another 7 days after your return. In summary: For short holidays set holiday_days_left to the number of full days you are away, including today but excluding the return day For longer holidays set holiday_days_left to the number of days you are away plus another 7 days until the data catches back up","title":"Holiday mode"},{"location":"customisation/#debug","text":"debug_enable when on prints lots of debug, leave off by default plan_debug ( expert mode ) when enabled adds some extra debug to the Predbat HTML plan","title":"Debug"},{"location":"developing/","text":"Developing on Predbat Creating a fork Using GitHub, take a fork of Predbat - effectively, this creates a copy of the main repository, but in your personal space. There, you can create branches to develop on. Pull requests Once you've completed your work on your branch, you can create a pull request (PR) to merge your work back in to the main branch of Predbat. This PR should describe the work you've done in a way that makes it easy for someone to review your work, and either add comments or approve it. Editing the code There are at least a couple of ways of working on the code, outlined here. Using GitHub Codespaces What is GitHub Codespaces? Especially if you don't need to have a running Home Assistant system to make the changes you're interested in (e.g. for documentation, quick fixes etc.) a really easy way to work on the code is using GitHub Codespaces. GitHub Codespaces gives you a full featured development environment. This includes: A full IDE (a code editor), Visual Studio Code, which can be: Run in the browser, requiring no additional software to be installed Run in a virtual machine (VM) running in the cloud which can connect to a copy of VS Code installed on your own machine A terminal where you can run commands against your codebase e.g. running pre-commit to run the automatic code quality checks, linting files, etc. Software like mkdocs to re-generate the documentation files (and other software we may include) pre-installed in it The Codespaces environment is entirely separate from your HA installation, so does not require any modification to your HA setup to work with it. However, you are modifying code in an environment where you can't see HA running, so it's great for things like updating documentation, or writing automated tests, but not if you need to see your changes live within HA. Running GitHub Codespaces You may with to first install VS Code on your machine, which does offer some benefits compared to running Codespaces in the cloud, but this is certainly not essential, and you'll see the same code editor and terminal, and you'll have the same commands and Python packages available in the terminal. The local installation is better in a small number of scenarios e.g. if you need to connect from your browser to a specific port on the VM, such as if you're working on the documentation. Importantly, even if you do a local install of VS Code and use that to edit your code within GitHub, the terminal, the code you're editing any commands that you run, and any processes like mkdocs that you may browse to are all running in the Codespaces VM. Your local VS Code is connected to the VM through SSH. It will appear as if the code, the terminal etc. are local, but they are not. Running a local VS Code install connected to Codespaces will not install Python, Python packages or anything else on your local machine. Now, from your fork or branch, click on the Code button, and select the Codespaces tab. You can create multiple environments, or use a single environment and swap between branches in it. Once you start your Codespaces environment, it'll take a minute to create a VM for you, and to install the software we've asked it to install in there. It will also clone your repository and chosen branch into it for you, and the VM will be authenticated with GitHub so you can commit and push straight back to your fork of Predbat on GitHub. You can choose between running the IDE in the browser, or having your local installation of VS Code connect to the environment that GitHub Codespaces has created for you. The Codespaces will be already set up with Python, along with various Python packages (as defined in requirements.txt ). The environment is configured through the config in .devcontainer/devcontainer.json . Developing locally within Home Assistant To be documented later. Working on the documentation Overview of the Predbat documentation The documentation site at https://springfall2008.github.io/batpred/ is built from Markdown files in this repo. The Markdown files used to build the documentation are in the docs/ folder, with additional config for building the documentation site in mkdocs.yml . If you're making minor changes to the documentation e.g. fixing a spelling, you can just edit the Markdown files directly, and it will be pushed to the main documentation site as outlined in the documentation build process section below, once your changes are merged into main and released. However, if you're doing more than that, e.g. adding new sections, working with lists etc. we recommend you follow the instructions in working locally on the documentation below, as this will give you a live preview of what the documentation will look like once it's build and published. This will avoid any unexpected results appearing in the main documentation site. If you are adding a new file, please ensure you add that file to mkdocs.yml , so it will be linked from the menu in the sidebar. The documentation build process The documentation for the site is built using mkdocs , which will already be installed if you're using a GitHub Codespaces environment. For a detailed explanation of mkdocs features, please read the mkdocs documentation . As briefly covered above, mkdocs.yml contains the config for defining the documentation site, and the documentation is built by mkdocs reading the Markdown files in the docs/ folder, and creating HTML files from those files. mkdocs can be used locally for previewing, but is also used as part of the documentation build process that publishes the official documentation site. The publishing of the documentation is triggered by a GitHub action, as defined in .github/workflows/main.yml . In short, after configuring the build environment, mkdocs builds the site, then pushes the HTML produced to the gh-pages branch, overwriting whatever was there previously. GitHub will then detect a new commit on the gh-pages branch, and that will trigger another action to run (as defined by GitHub). This action will take the HTML files on the gh-pages branch, and will make it available at https://springfall2008.github.io/batpred/ . The documentation will be published as it is, with no further review process, so please ensure you check the documentation that will be built before merging it in. Working locally on the documentation If you are making changes to the documentation, you can see a live preview version of the documentation as it will be built and deployed. This preview version is local to your environment, is temporary, and does not impact the published version in any way. It's recommended for anything other than simple changes like fixing spellings, adding a sentence or two. Things like new sections, lists, new pages etc. are best previewed due to the complications of various Markdown standards, as what works on GitHub READMEs, for example, does not necessarily work with the published documentation site (which follows a more strict Markdown standard). There are a number of terminal commands that you can use in the Codespaces environment. Open a terminal window in Codespaces by choosing menu > Terminal > New Terminal. To run the live preview, enter mkdocs serve in the terminal window - this will cause mkdocs to build a local temporary version of the documentation site, and to temporarily publish it on port 8000 - it will show the link where you can access the documentation. Also, it will watch the docs/ folder, and any time you change the files, it will rebuild the site, allowing you to see changes to the Markdown files in your browser within a few seconds. The site will continue being served until you press CTRL-C to end the mkdocs serve command. Note, accessing the site published by mkdocs serve is not possible if you are using Codespaces to run VS Code in the browser, but it is possible if you're using it via VS Code running locally, due to the way in which ports on your environment are shared. Coding standards Expected standards This section will be enhanced following discussions as we go. However, here's a starting point: Variable names should be lower_case_with_underscores - this fits with most existing variables, is a common standard for Python code, and also allows the spell checking to check individual words within the variable name. Enforced standards Certain coding standards are enforced within the repository. Some of them can be auto-fixed, if you do a commit that fails one of those standards; other issues will need fixing first, as your pull request won't merge in GitHub until it passes. These standards are enforced by pre-commit , a tool which is able to run other tools to check, and potentially fix (for certain types of issues) any mistakes you've made. The .pre-commit-config.yaml file lists all checks that are currently carried out within the repository. Bear in mind that these checks are done according to the config within that file in the branch that you are working in, so if someone adds a new check, or changes some of the related settings, it won't apply on your branch until you've merged in their changes. Some of the tools have their own related config files: CSpell - .cspell.json and .cspell/custom-dictionary-workspace.txt Black - pyproject.toml Markdown Lint - .markdownlint.jsonc Additional notes on some of the standards: CSpell - if you have the spelling check failing due to a word which is valid but is not in the in-built dictionary, please add that word to the end of .cspell/custom-dictionary-workspace.txt and stage those changes. The spell-check should then pass. Note, the dictionary file will get re-sorted alphabetically when you run pre-commit , so you'll need to re-stage the file after it's been sorted. Running the checks locally If you are using a Codespaces environment, you'll already have pre-commit installed automatically. You can run it manually, or automatically. Running pre-commit manually: In a terminal window, running pre-commit will run all the checks against any files that you have modified and staged. Alternatively, running pre-commit run --all-files will run all the checks against all files within the repository. Note that if pre-commit makes any changes to any files when it runs, those changes will not be staged. You will need to stage those changes too before committing. You may notice pre-commit mentioning about stashing changes - this is because when it runs, any changes that aren't staged are stashed (saved away temporarily) so it runs against only the staged changes; after it has run, it pulls back those stashed changes, so they appear again (still unstaged). Running pre-commit automatically: If you run pre-commit install in a terminal window it will install a pre-commit hook - this is a file which tells git to run some code each type you do a particular action (a pre-commit hook runs at the start of processing a commit, but there are other hooks e.g. pre-push). Now, any time you perform a commit, pre-commit will run automatically on the staged files - this is a handy way of making sure that you don't accidentally commit code which will fail checks later. You can still run it manually as outlined above, in addition to the automated checks that it will do on commits. Running the checks from within GitHub When commits are done on pull requests, and in any other scenarios added to the on section of .github/workflows/linting.yml , the GitHub Actions in that file will run. In particular, the pre-commit.ci lite action will run. This uses the code here to run the same checks that get run locally (as described in the .pre-commit-config.yaml file). This will cause your commit, branch or pull request to get either a green tick or a red cross against it, to show whether the code passed the checks or not. This will happen automatically, when you push code on a branch that has a pull request. In addition, if pre-commit finds any errors that it is able to fix (e.g. a missing blank line at the end of a file, or trailing whitespace), it will do a commit of its own to fix those problems, and will push that commit back to your branch on GitHub. This will then trigger another run, which should now pass. Note : This means that pre-commit will be adding commits to your branch - this will need you to be pulling changes from GitHub so you pick up the changes that have been added by pre-commit otherwise you will hit a problem when you next try to push a commit on your branch. You can pull in those changes by running git pull , which is the equivalent of running git fetch then git merge . This is no different to working on the same branch with another developer, but it will be different to the workflow most of us have when working on Predbat.","title":"Developing on Predbat"},{"location":"developing/#developing-on-predbat","text":"","title":"Developing on Predbat"},{"location":"developing/#creating-a-fork","text":"Using GitHub, take a fork of Predbat - effectively, this creates a copy of the main repository, but in your personal space. There, you can create branches to develop on.","title":"Creating a fork"},{"location":"developing/#pull-requests","text":"Once you've completed your work on your branch, you can create a pull request (PR) to merge your work back in to the main branch of Predbat. This PR should describe the work you've done in a way that makes it easy for someone to review your work, and either add comments or approve it.","title":"Pull requests"},{"location":"developing/#editing-the-code","text":"There are at least a couple of ways of working on the code, outlined here.","title":"Editing the code"},{"location":"developing/#using-github-codespaces","text":"","title":"Using GitHub Codespaces"},{"location":"developing/#what-is-github-codespaces","text":"Especially if you don't need to have a running Home Assistant system to make the changes you're interested in (e.g. for documentation, quick fixes etc.) a really easy way to work on the code is using GitHub Codespaces. GitHub Codespaces gives you a full featured development environment. This includes: A full IDE (a code editor), Visual Studio Code, which can be: Run in the browser, requiring no additional software to be installed Run in a virtual machine (VM) running in the cloud which can connect to a copy of VS Code installed on your own machine A terminal where you can run commands against your codebase e.g. running pre-commit to run the automatic code quality checks, linting files, etc. Software like mkdocs to re-generate the documentation files (and other software we may include) pre-installed in it The Codespaces environment is entirely separate from your HA installation, so does not require any modification to your HA setup to work with it. However, you are modifying code in an environment where you can't see HA running, so it's great for things like updating documentation, or writing automated tests, but not if you need to see your changes live within HA.","title":"What is GitHub Codespaces?"},{"location":"developing/#running-github-codespaces","text":"You may with to first install VS Code on your machine, which does offer some benefits compared to running Codespaces in the cloud, but this is certainly not essential, and you'll see the same code editor and terminal, and you'll have the same commands and Python packages available in the terminal. The local installation is better in a small number of scenarios e.g. if you need to connect from your browser to a specific port on the VM, such as if you're working on the documentation. Importantly, even if you do a local install of VS Code and use that to edit your code within GitHub, the terminal, the code you're editing any commands that you run, and any processes like mkdocs that you may browse to are all running in the Codespaces VM. Your local VS Code is connected to the VM through SSH. It will appear as if the code, the terminal etc. are local, but they are not. Running a local VS Code install connected to Codespaces will not install Python, Python packages or anything else on your local machine. Now, from your fork or branch, click on the Code button, and select the Codespaces tab. You can create multiple environments, or use a single environment and swap between branches in it. Once you start your Codespaces environment, it'll take a minute to create a VM for you, and to install the software we've asked it to install in there. It will also clone your repository and chosen branch into it for you, and the VM will be authenticated with GitHub so you can commit and push straight back to your fork of Predbat on GitHub. You can choose between running the IDE in the browser, or having your local installation of VS Code connect to the environment that GitHub Codespaces has created for you. The Codespaces will be already set up with Python, along with various Python packages (as defined in requirements.txt ). The environment is configured through the config in .devcontainer/devcontainer.json .","title":"Running GitHub Codespaces"},{"location":"developing/#developing-locally-within-home-assistant","text":"To be documented later.","title":"Developing locally within Home Assistant"},{"location":"developing/#working-on-the-documentation","text":"","title":"Working on the documentation"},{"location":"developing/#overview-of-the-predbat-documentation","text":"The documentation site at https://springfall2008.github.io/batpred/ is built from Markdown files in this repo. The Markdown files used to build the documentation are in the docs/ folder, with additional config for building the documentation site in mkdocs.yml . If you're making minor changes to the documentation e.g. fixing a spelling, you can just edit the Markdown files directly, and it will be pushed to the main documentation site as outlined in the documentation build process section below, once your changes are merged into main and released. However, if you're doing more than that, e.g. adding new sections, working with lists etc. we recommend you follow the instructions in working locally on the documentation below, as this will give you a live preview of what the documentation will look like once it's build and published. This will avoid any unexpected results appearing in the main documentation site. If you are adding a new file, please ensure you add that file to mkdocs.yml , so it will be linked from the menu in the sidebar.","title":"Overview of the Predbat documentation"},{"location":"developing/#the-documentation-build-process","text":"The documentation for the site is built using mkdocs , which will already be installed if you're using a GitHub Codespaces environment. For a detailed explanation of mkdocs features, please read the mkdocs documentation . As briefly covered above, mkdocs.yml contains the config for defining the documentation site, and the documentation is built by mkdocs reading the Markdown files in the docs/ folder, and creating HTML files from those files. mkdocs can be used locally for previewing, but is also used as part of the documentation build process that publishes the official documentation site. The publishing of the documentation is triggered by a GitHub action, as defined in .github/workflows/main.yml . In short, after configuring the build environment, mkdocs builds the site, then pushes the HTML produced to the gh-pages branch, overwriting whatever was there previously. GitHub will then detect a new commit on the gh-pages branch, and that will trigger another action to run (as defined by GitHub). This action will take the HTML files on the gh-pages branch, and will make it available at https://springfall2008.github.io/batpred/ . The documentation will be published as it is, with no further review process, so please ensure you check the documentation that will be built before merging it in.","title":"The documentation build process"},{"location":"developing/#working-locally-on-the-documentation","text":"If you are making changes to the documentation, you can see a live preview version of the documentation as it will be built and deployed. This preview version is local to your environment, is temporary, and does not impact the published version in any way. It's recommended for anything other than simple changes like fixing spellings, adding a sentence or two. Things like new sections, lists, new pages etc. are best previewed due to the complications of various Markdown standards, as what works on GitHub READMEs, for example, does not necessarily work with the published documentation site (which follows a more strict Markdown standard). There are a number of terminal commands that you can use in the Codespaces environment. Open a terminal window in Codespaces by choosing menu > Terminal > New Terminal. To run the live preview, enter mkdocs serve in the terminal window - this will cause mkdocs to build a local temporary version of the documentation site, and to temporarily publish it on port 8000 - it will show the link where you can access the documentation. Also, it will watch the docs/ folder, and any time you change the files, it will rebuild the site, allowing you to see changes to the Markdown files in your browser within a few seconds. The site will continue being served until you press CTRL-C to end the mkdocs serve command. Note, accessing the site published by mkdocs serve is not possible if you are using Codespaces to run VS Code in the browser, but it is possible if you're using it via VS Code running locally, due to the way in which ports on your environment are shared.","title":"Working locally on the documentation"},{"location":"developing/#coding-standards","text":"","title":"Coding standards"},{"location":"developing/#expected-standards","text":"This section will be enhanced following discussions as we go. However, here's a starting point: Variable names should be lower_case_with_underscores - this fits with most existing variables, is a common standard for Python code, and also allows the spell checking to check individual words within the variable name.","title":"Expected standards"},{"location":"developing/#enforced-standards","text":"Certain coding standards are enforced within the repository. Some of them can be auto-fixed, if you do a commit that fails one of those standards; other issues will need fixing first, as your pull request won't merge in GitHub until it passes. These standards are enforced by pre-commit , a tool which is able to run other tools to check, and potentially fix (for certain types of issues) any mistakes you've made. The .pre-commit-config.yaml file lists all checks that are currently carried out within the repository. Bear in mind that these checks are done according to the config within that file in the branch that you are working in, so if someone adds a new check, or changes some of the related settings, it won't apply on your branch until you've merged in their changes. Some of the tools have their own related config files: CSpell - .cspell.json and .cspell/custom-dictionary-workspace.txt Black - pyproject.toml Markdown Lint - .markdownlint.jsonc Additional notes on some of the standards: CSpell - if you have the spelling check failing due to a word which is valid but is not in the in-built dictionary, please add that word to the end of .cspell/custom-dictionary-workspace.txt and stage those changes. The spell-check should then pass. Note, the dictionary file will get re-sorted alphabetically when you run pre-commit , so you'll need to re-stage the file after it's been sorted.","title":"Enforced standards"},{"location":"developing/#running-the-checks-locally","text":"If you are using a Codespaces environment, you'll already have pre-commit installed automatically. You can run it manually, or automatically. Running pre-commit manually: In a terminal window, running pre-commit will run all the checks against any files that you have modified and staged. Alternatively, running pre-commit run --all-files will run all the checks against all files within the repository. Note that if pre-commit makes any changes to any files when it runs, those changes will not be staged. You will need to stage those changes too before committing. You may notice pre-commit mentioning about stashing changes - this is because when it runs, any changes that aren't staged are stashed (saved away temporarily) so it runs against only the staged changes; after it has run, it pulls back those stashed changes, so they appear again (still unstaged). Running pre-commit automatically: If you run pre-commit install in a terminal window it will install a pre-commit hook - this is a file which tells git to run some code each type you do a particular action (a pre-commit hook runs at the start of processing a commit, but there are other hooks e.g. pre-push). Now, any time you perform a commit, pre-commit will run automatically on the staged files - this is a handy way of making sure that you don't accidentally commit code which will fail checks later. You can still run it manually as outlined above, in addition to the automated checks that it will do on commits.","title":"Running the checks locally"},{"location":"developing/#running-the-checks-from-within-github","text":"When commits are done on pull requests, and in any other scenarios added to the on section of .github/workflows/linting.yml , the GitHub Actions in that file will run. In particular, the pre-commit.ci lite action will run. This uses the code here to run the same checks that get run locally (as described in the .pre-commit-config.yaml file). This will cause your commit, branch or pull request to get either a green tick or a red cross against it, to show whether the code passed the checks or not. This will happen automatically, when you push code on a branch that has a pull request. In addition, if pre-commit finds any errors that it is able to fix (e.g. a missing blank line at the end of a file, or trailing whitespace), it will do a commit of its own to fix those problems, and will push that commit back to your branch on GitHub. This will then trigger another run, which should now pass. Note : This means that pre-commit will be adding commits to your branch - this will need you to be pulling changes from GitHub so you pick up the changes that have been added by pre-commit otherwise you will hit a problem when you next try to push a commit on your branch. You can pull in those changes by running git pull , which is the equivalent of running git fetch then git merge . This is no different to working on the same branch with another developer, but it will be different to the workflow most of us have when working on Predbat.","title":"Running the checks from within GitHub"},{"location":"energy-rates/","text":"Energy rates Predbat needs to know what your Import and (optionally) Export rates are so it can plan the optimal way to use your battery. Your Import and Export rates can be simple flat rates, more complex time of day tariffs (e.g. Economy 7, Octopus Flux), or daily/half-hourly rates that track electricity market prices (e.g. Octopus Agile or Tracker). Energy rates are all configured in the apps.yaml file that's stored in either the /addon_configs/46f69597_appdaemon-predbat/apps or the /config/appdaemon/apps/batpred/config/ directory depending on what type of Predbat installation method you have used . You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) to edit this file - see editing configuration files within Home Assistant if you need to install an editor. Octopus Energy integration If your electricity supplier is Octopus Energy then the simplest way to provide Predbat with your electricity pricing information is to use the Octopus Energy integration . The Octopus Energy integration connects to your Octopus Energy account and retrieves the tariffs you are on, and the current tariff rates. If you change tariff within Octopus the integration will automatically retrieve the updated tariff information, and as tariff prices change, again they are automatically retrieved. The integration also provides support for Intelligent Octopus charging to support car charging. Follow the instructions provided in the Octopus Energy integration documentation to install and setup the integration. Once installed, you will need to configure the integration (go to Settings / Devices & Services / Integrations / Octopus Energy then click 'Configure') and provide the integration with your 'Octopus API key' (that you obtain from your Octopus account : Personal Details / API access). CAUTION To get detailed energy rates needed by Predbat you need to go into Home Assistant and manually enable the following Octopus Energy events which are disabled by default when the integration is installed: event.octopus_energy_electricity_xxxxxxxx_previous_day_rates event.octopus_energy_electricity_xxxxxxxx_current_day_rates event.octopus_energy_electricity_xxxxxxxx_next_day_rates event.octopus_energy_electricity_xxxxxxxx_export_previous_day_rates event.octopus_energy_electricity_xxxxxxxx_export_current_day_rates event.octopus_energy_electricity_xxxxxxxx_export_next_day_rates event.octopus_energy_gas_xxxxxxxx_previous_day_rates event.octopus_energy_gas_xxxxxxxx_current_day_rates event.octopus_energy_gas_xxxxxxxx_next_day_rates To enable the above events: Go to Settings / Devices & Services / Integrations, choose Octopus Energy, then xx entities You will see a list of entities (and events) supplied by the Octopus integration Click the 'Filter' symbol on the top right hand corner (a series of lines in a downwards pointing arrow) and make sure all the options are selected Then in the left hand-side search entities box, type \"current_day\" Click on the first event that comes up, check the name is the right one Click the cog wheel, then you should see the option to enable the event Click the option to enable the event and press 'Update' to make the change Repeat this for the other events. The gas rates are only required if you have a gas boiler, an iBoost, and are using Predbat to determine whether it's cheaper to heat your hot water with the iBoost or via gas. Verify that the integration is working correctly in Home Assistant by going to Developer Tools / States, and enter 'octopus' in the 'Filter entities' box. Confirm that the Octopus entities are being populated correctly. Configuring Predbat to use the Octopus Energy integration The following configuration items in apps.yaml are used to configure Predbat to use the Octopus Energy integration. They are set to a regular expression and should be auto-discovered so that Predbat automatically uses the Octopus Energy integration, but you can comment out the regular expression lines to disable, or you set them manually. metric_octopus_import - Import rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_electricity_ _current_rate metric_octopus_export - Export rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_electricity_ _export_current_rate metric_octopus_gas - Gas rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_gas_ _current_rate octopus_intelligent_slot - If you have the Octopus Intelligent GO tariff this should point to the 'slot' sensor binary_sensor.octopus_energy_ _intelligent_dispatching metric_octopus_gas is (as above) only required to be configured if you are using Predbat to determine whether to heat your hot water via your iBoost or gas. If you do not have an export rate, or are not on the Octopus Go tariff, then the appropriate lines can be commented out in apps.yaml. Standing charge Predbat can also (optionally) include the daily standing charge in cost predictions. The following configuration item in apps.yaml defaults to obtaining the standing charge from the Octopus Energy integration: metric_standing_charge - Standing charge in pounds. By default points to the Octopus Energy integration sensor sensor.octopus_energy_electricity_ _current_standing_charge You can manually change this to a standing charge in pounds, e.g. 0.50 is 50p, or delete this line from apps.yaml, or set it to zero if you don't want the standing charge (and only have consumption usage) to be included in Predbat charts and output data. Octopus Saving sessions Predbat is able to automatically join you to Octopus saving sessions and plan battery activity for the saving session period to maximise your income. For Predbat to automatically manage Octopus saving sessions the following additional configuration item in apps.yaml is used. Like the electricity rates this is set in the apps.yaml template to a regular expression that should auto-discover the Octopus Energy integration. octopus_saving_session - Indicates if a saving session is active, should point to the sensor binary_sensor.octopus_energy_ _octoplus_saving_sessions. When a saving session is available it will be automatically joined by Predbat and should then appear as a joined session within the next 30 minutes. In the Predbat plan, for joined saving sessions the energy rates for import and export will be overridden by adding the assumed saving rate to your normal rate. The assumed rate will be taken from the Octopus Energy integration and converted into pence using the octopus_saving_session_octopoints_per_penny configuration item in apps.yaml (default is 8). As the saving session import and export rates are very high compared to normal Predbat will plan additional export during the saving session period. If necessary, a pre-charge may happen at some point during the day to maintain the battery right level for the session. Note that Predbat's operational mode select.predbat_mode must be set to either 'Control charge' or 'Control charge & discharge' for Predbat to be able to manage the battery for the saving session. If you do not have an export tariff then forced export will not apply and Predbat will just ensure you have enough battery charge to see you through the saving session period. If you do not want Predbat to automatically join Octopus saving sessions and manage your battery activity for the session, simply delete or comment out the octopus_saving_session entry in apps.yaml. Octopus Rates URL If you do not wish to use the Octopus Energy integration and are an Octopus Energy customer then you can configure Predbat to get the electricity rates directly online from the Octopus website. In apps.yaml configure the following lines: rates_import_octopus_url to point to the appropriate import tariff URL on the Octopus website rates_export_octopus_url to point to the export tariff URL e.g. rates_import_octopus_url : \"https://api.octopus.energy/v1/products/FLUX-IMPORT-23-02-14/electricity-tariffs/E-1R-FLUX-IMPORT-23-02-14-A/standard-unit-rates\" rates_import_octopus_url : \"https://api.octopus.energy/v1/products/AGILE-FLEX-BB-23-02-08/electricity-tariffs/E-1R-AGILE-FLEX-BB-23-02-08-A/standard-unit-rates\" rates_export_octopus_url: \"https://api.octopus.energy/v1/products/FLUX-EXPORT-BB-23-02-14/electricity-tariffs/E-1R-FLUX-EXPORT-BB-23-02-14-A/standard-unit-rates\" rates_export_octopus_url: \"https://api.octopus.energy/v1/products/AGILE-OUTGOING-BB-23-02-28/electricity-tariffs/E-1R-AGILE-OUTGOING-BB-23-02-28-A/standard-unit-rates/\" rates_export_octopus_url: \"https://api.octopus.energy/v1/products/OUTGOING-FIX-12M-BB-23-02-09/electricity-tariffs/E-1R-OUTGOING-FIX-12M-BB-23-02-09-A/standard-unit-rates/\" If you configure the rates_import_octopus_url then Predbat will use this instead of metric_octopus or rates_import. Similarly rates_export_octopus_url takes precedence over metric_octopus_export or rates_export. Configuring the Octopus rates URL is an expert feature and for most users the Octopus Energy integration is a simpler solution to use. Rate Bands to manually configure Energy Rates If you are not an Octopus Energy customer, or you are but your energy rates repeat in a simple manner, you can configure your rate bands in apps.yaml using rates_import/rates_export. Add the following entries to apps.yaml to define the pattern of rates over a 24-hour period: rates_import: - start: \"HH:MM:SS\" end: \"HH:MM:SS\" rate: pence rates_export: - start: \"HH:MM:SS\" end: \"HH:MM:SS\" rate: pence start and end are in the time format of \"HH:MM:SS\" e.g. \"12:30:00\" and should be aligned to 30 minute slots normally. rate is in pence e.g. 4.2 start and end can be omitted and Predbat will assume that you are on a single flat rate tariff. If there are any gaps in the 24-hour period then a zero rate will be assumed. Manually over-riding energy rates You can also override the energy rates (regardless of whether they are set manually or via the Octopus Energy integration) by using the override feature in apps.yaml. Rate override is used to set the specific date and time period where your rates are different, e.g. an Octopus Power Up session (zero rate for an hour or two), or the British Gas half-price electricity on Sunday's. Unfortunately there aren't any API's available to feed this information automatically into Predbat so you will have to edit apps.yaml manually to set the appropriate rate over-ride dates and times: rates_import_override: - date : \"YYYY-MM-DD\" start : \"HH:MM:SS\" end : \"HH:MM:SS\" rate : pence rates_export_override: - date : \"YYYY-MM-DD\" start : \"HH:MM:SS\" end : \"HH:MM:SS\" rate : pence date is in the date format of \"YYYY-MM-DD\" e.g. \"2023-09-09\", start and end in \"HH:MM:SS\" time format e.g. \"12:30:00\", and rate in pence. Rate offsets If you are on an Agile or Tracker tariff you can tune future unknown energy rates by adjusting the entities input_number.predbat_metric_future_rate_offset_import ( expert mode ) and input_number.predbat_metric_future_rate_offset_export ( expert mode ) inside Home Assistant to set the predicted offset for future unknown rates. Future Agile energy rates In the energy market it's possible to calculate the Octopus Agile rates from around 10am UK time using public data, you can enable this in apps.yaml for Import, Export or both. This will approximate next day's rates based on the spot prices. The approximation is only used until the real Octopus Agile rates are released around 4pm. futurerate_url - URL of future energy market prices; this should not normally need to be changed futurerate_adjust_import and futurerate_adjust_export - Whether tomorrow's predicted import or export prices should be adjusted based on energy market prices or not. Set these depending upon whether you have an agile tariff for import, export or both futurerate_peak_start and futurerate_peak_end - during the peak period Octopus apply an additional peak-rate price adjustment. These configuration items enable the peak-rate hours to be adjusted futurerate_peak_premium_import and futurerate_peak_premium_export - the price premium (in pence) to be added to the energy market prices during the above-defined peak period CAUTION: You may violate the terms and conditions of the Nordpool site if you use this data and as such the authors of Predbat accept no responsibility for any violations: https://www.nordpoolgroup.com/en/About-us/terms-and-conditions-for-useofwebsite/ futurerate_url: '' futurerate_adjust_import: True futurerate_adjust_export: False futurerate_peak_start: \"16:00:00\" futurerate_peak_end: \"19:00:00\" futurerate_peak_premium_import: 14 futurerate_peak_premium_export: 6.5","title":"Energy rates"},{"location":"energy-rates/#energy-rates","text":"Predbat needs to know what your Import and (optionally) Export rates are so it can plan the optimal way to use your battery. Your Import and Export rates can be simple flat rates, more complex time of day tariffs (e.g. Economy 7, Octopus Flux), or daily/half-hourly rates that track electricity market prices (e.g. Octopus Agile or Tracker). Energy rates are all configured in the apps.yaml file that's stored in either the /addon_configs/46f69597_appdaemon-predbat/apps or the /config/appdaemon/apps/batpred/config/ directory depending on what type of Predbat installation method you have used . You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) to edit this file - see editing configuration files within Home Assistant if you need to install an editor.","title":"Energy rates"},{"location":"energy-rates/#octopus-energy-integration","text":"If your electricity supplier is Octopus Energy then the simplest way to provide Predbat with your electricity pricing information is to use the Octopus Energy integration . The Octopus Energy integration connects to your Octopus Energy account and retrieves the tariffs you are on, and the current tariff rates. If you change tariff within Octopus the integration will automatically retrieve the updated tariff information, and as tariff prices change, again they are automatically retrieved. The integration also provides support for Intelligent Octopus charging to support car charging. Follow the instructions provided in the Octopus Energy integration documentation to install and setup the integration. Once installed, you will need to configure the integration (go to Settings / Devices & Services / Integrations / Octopus Energy then click 'Configure') and provide the integration with your 'Octopus API key' (that you obtain from your Octopus account : Personal Details / API access). CAUTION To get detailed energy rates needed by Predbat you need to go into Home Assistant and manually enable the following Octopus Energy events which are disabled by default when the integration is installed: event.octopus_energy_electricity_xxxxxxxx_previous_day_rates event.octopus_energy_electricity_xxxxxxxx_current_day_rates event.octopus_energy_electricity_xxxxxxxx_next_day_rates event.octopus_energy_electricity_xxxxxxxx_export_previous_day_rates event.octopus_energy_electricity_xxxxxxxx_export_current_day_rates event.octopus_energy_electricity_xxxxxxxx_export_next_day_rates event.octopus_energy_gas_xxxxxxxx_previous_day_rates event.octopus_energy_gas_xxxxxxxx_current_day_rates event.octopus_energy_gas_xxxxxxxx_next_day_rates To enable the above events: Go to Settings / Devices & Services / Integrations, choose Octopus Energy, then xx entities You will see a list of entities (and events) supplied by the Octopus integration Click the 'Filter' symbol on the top right hand corner (a series of lines in a downwards pointing arrow) and make sure all the options are selected Then in the left hand-side search entities box, type \"current_day\" Click on the first event that comes up, check the name is the right one Click the cog wheel, then you should see the option to enable the event Click the option to enable the event and press 'Update' to make the change Repeat this for the other events. The gas rates are only required if you have a gas boiler, an iBoost, and are using Predbat to determine whether it's cheaper to heat your hot water with the iBoost or via gas. Verify that the integration is working correctly in Home Assistant by going to Developer Tools / States, and enter 'octopus' in the 'Filter entities' box. Confirm that the Octopus entities are being populated correctly.","title":"Octopus Energy integration"},{"location":"energy-rates/#configuring-predbat-to-use-the-octopus-energy-integration","text":"The following configuration items in apps.yaml are used to configure Predbat to use the Octopus Energy integration. They are set to a regular expression and should be auto-discovered so that Predbat automatically uses the Octopus Energy integration, but you can comment out the regular expression lines to disable, or you set them manually. metric_octopus_import - Import rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_electricity_ _current_rate metric_octopus_export - Export rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_electricity_ _export_current_rate metric_octopus_gas - Gas rates from the Octopus Energy integration, should point to the sensor sensor.octopus_energy_gas_ _current_rate octopus_intelligent_slot - If you have the Octopus Intelligent GO tariff this should point to the 'slot' sensor binary_sensor.octopus_energy_ _intelligent_dispatching metric_octopus_gas is (as above) only required to be configured if you are using Predbat to determine whether to heat your hot water via your iBoost or gas. If you do not have an export rate, or are not on the Octopus Go tariff, then the appropriate lines can be commented out in apps.yaml.","title":"Configuring Predbat to use the Octopus Energy integration"},{"location":"energy-rates/#standing-charge","text":"Predbat can also (optionally) include the daily standing charge in cost predictions. The following configuration item in apps.yaml defaults to obtaining the standing charge from the Octopus Energy integration: metric_standing_charge - Standing charge in pounds. By default points to the Octopus Energy integration sensor sensor.octopus_energy_electricity_ _current_standing_charge You can manually change this to a standing charge in pounds, e.g. 0.50 is 50p, or delete this line from apps.yaml, or set it to zero if you don't want the standing charge (and only have consumption usage) to be included in Predbat charts and output data.","title":"Standing charge"},{"location":"energy-rates/#octopus-saving-sessions","text":"Predbat is able to automatically join you to Octopus saving sessions and plan battery activity for the saving session period to maximise your income. For Predbat to automatically manage Octopus saving sessions the following additional configuration item in apps.yaml is used. Like the electricity rates this is set in the apps.yaml template to a regular expression that should auto-discover the Octopus Energy integration. octopus_saving_session - Indicates if a saving session is active, should point to the sensor binary_sensor.octopus_energy_ _octoplus_saving_sessions. When a saving session is available it will be automatically joined by Predbat and should then appear as a joined session within the next 30 minutes. In the Predbat plan, for joined saving sessions the energy rates for import and export will be overridden by adding the assumed saving rate to your normal rate. The assumed rate will be taken from the Octopus Energy integration and converted into pence using the octopus_saving_session_octopoints_per_penny configuration item in apps.yaml (default is 8). As the saving session import and export rates are very high compared to normal Predbat will plan additional export during the saving session period. If necessary, a pre-charge may happen at some point during the day to maintain the battery right level for the session. Note that Predbat's operational mode select.predbat_mode must be set to either 'Control charge' or 'Control charge & discharge' for Predbat to be able to manage the battery for the saving session. If you do not have an export tariff then forced export will not apply and Predbat will just ensure you have enough battery charge to see you through the saving session period. If you do not want Predbat to automatically join Octopus saving sessions and manage your battery activity for the session, simply delete or comment out the octopus_saving_session entry in apps.yaml.","title":"Octopus Saving sessions"},{"location":"energy-rates/#octopus-rates-url","text":"If you do not wish to use the Octopus Energy integration and are an Octopus Energy customer then you can configure Predbat to get the electricity rates directly online from the Octopus website. In apps.yaml configure the following lines: rates_import_octopus_url to point to the appropriate import tariff URL on the Octopus website rates_export_octopus_url to point to the export tariff URL e.g. rates_import_octopus_url : \"https://api.octopus.energy/v1/products/FLUX-IMPORT-23-02-14/electricity-tariffs/E-1R-FLUX-IMPORT-23-02-14-A/standard-unit-rates\" rates_import_octopus_url : \"https://api.octopus.energy/v1/products/AGILE-FLEX-BB-23-02-08/electricity-tariffs/E-1R-AGILE-FLEX-BB-23-02-08-A/standard-unit-rates\" rates_export_octopus_url: \"https://api.octopus.energy/v1/products/FLUX-EXPORT-BB-23-02-14/electricity-tariffs/E-1R-FLUX-EXPORT-BB-23-02-14-A/standard-unit-rates\" rates_export_octopus_url: \"https://api.octopus.energy/v1/products/AGILE-OUTGOING-BB-23-02-28/electricity-tariffs/E-1R-AGILE-OUTGOING-BB-23-02-28-A/standard-unit-rates/\" rates_export_octopus_url: \"https://api.octopus.energy/v1/products/OUTGOING-FIX-12M-BB-23-02-09/electricity-tariffs/E-1R-OUTGOING-FIX-12M-BB-23-02-09-A/standard-unit-rates/\" If you configure the rates_import_octopus_url then Predbat will use this instead of metric_octopus or rates_import. Similarly rates_export_octopus_url takes precedence over metric_octopus_export or rates_export. Configuring the Octopus rates URL is an expert feature and for most users the Octopus Energy integration is a simpler solution to use.","title":"Octopus Rates URL"},{"location":"energy-rates/#rate-bands-to-manually-configure-energy-rates","text":"If you are not an Octopus Energy customer, or you are but your energy rates repeat in a simple manner, you can configure your rate bands in apps.yaml using rates_import/rates_export. Add the following entries to apps.yaml to define the pattern of rates over a 24-hour period: rates_import: - start: \"HH:MM:SS\" end: \"HH:MM:SS\" rate: pence rates_export: - start: \"HH:MM:SS\" end: \"HH:MM:SS\" rate: pence start and end are in the time format of \"HH:MM:SS\" e.g. \"12:30:00\" and should be aligned to 30 minute slots normally. rate is in pence e.g. 4.2 start and end can be omitted and Predbat will assume that you are on a single flat rate tariff. If there are any gaps in the 24-hour period then a zero rate will be assumed.","title":"Rate Bands to manually configure Energy Rates"},{"location":"energy-rates/#manually-over-riding-energy-rates","text":"You can also override the energy rates (regardless of whether they are set manually or via the Octopus Energy integration) by using the override feature in apps.yaml. Rate override is used to set the specific date and time period where your rates are different, e.g. an Octopus Power Up session (zero rate for an hour or two), or the British Gas half-price electricity on Sunday's. Unfortunately there aren't any API's available to feed this information automatically into Predbat so you will have to edit apps.yaml manually to set the appropriate rate over-ride dates and times: rates_import_override: - date : \"YYYY-MM-DD\" start : \"HH:MM:SS\" end : \"HH:MM:SS\" rate : pence rates_export_override: - date : \"YYYY-MM-DD\" start : \"HH:MM:SS\" end : \"HH:MM:SS\" rate : pence date is in the date format of \"YYYY-MM-DD\" e.g. \"2023-09-09\", start and end in \"HH:MM:SS\" time format e.g. \"12:30:00\", and rate in pence.","title":"Manually over-riding energy rates"},{"location":"energy-rates/#rate-offsets","text":"If you are on an Agile or Tracker tariff you can tune future unknown energy rates by adjusting the entities input_number.predbat_metric_future_rate_offset_import ( expert mode ) and input_number.predbat_metric_future_rate_offset_export ( expert mode ) inside Home Assistant to set the predicted offset for future unknown rates.","title":"Rate offsets"},{"location":"energy-rates/#future-agile-energy-rates","text":"In the energy market it's possible to calculate the Octopus Agile rates from around 10am UK time using public data, you can enable this in apps.yaml for Import, Export or both. This will approximate next day's rates based on the spot prices. The approximation is only used until the real Octopus Agile rates are released around 4pm. futurerate_url - URL of future energy market prices; this should not normally need to be changed futurerate_adjust_import and futurerate_adjust_export - Whether tomorrow's predicted import or export prices should be adjusted based on energy market prices or not. Set these depending upon whether you have an agile tariff for import, export or both futurerate_peak_start and futurerate_peak_end - during the peak period Octopus apply an additional peak-rate price adjustment. These configuration items enable the peak-rate hours to be adjusted futurerate_peak_premium_import and futurerate_peak_premium_export - the price premium (in pence) to be added to the energy market prices during the above-defined peak period CAUTION: You may violate the terms and conditions of the Nordpool site if you use this data and as such the authors of Predbat accept no responsibility for any violations: https://www.nordpoolgroup.com/en/About-us/terms-and-conditions-for-useofwebsite/ futurerate_url: '' futurerate_adjust_import: True futurerate_adjust_export: False futurerate_peak_start: \"16:00:00\" futurerate_peak_end: \"19:00:00\" futurerate_peak_premium_import: 14 futurerate_peak_premium_export: 6.5","title":"Future Agile energy rates"},{"location":"faq/","text":"FAQ I've installed Predbat but I don't see the correct entities First look at predbat.status in Home Assistant and the AppDaemon.log (which can be found in the list of log files in the System/Log area of the GUI). See if any errors are warnings are found. If you see an error it's likely something is configured wrongly, check your entity settings are correct. Make sure Solcast is installed and it's auto-updated at least a couple of times a day (see the Solcast instructions ). The default solcast sensor names maybe wrong, you might need to update the apps.yaml config to match your own names (some people don't have the solcast_ bit in their names) Did you configure AppDaemon apps_dir correctly in appdaemon.yaml ? Why is my predicted charge % higher or lower than I might expect? Predbat is based on costing, so it will try to save you money. If you have the PV 10% option enabled it will also take into account the more worse case scenario and how often it might happen, so if the forecast is a bit unreliable it's better to charge more and not risk getting stung importing. Have you checked your energy rates for import and export are correct, maybe check the rates graph and confirm. If you do something like have export>import then Predbat will try to export as much as possible. Have you tuned Solcast to match your output accurately? Have you tuned best_soc_keep settings Do you have predicted car charging during the time period? You can also tune load_scaling and pv_scaling to adjust predictions up and down a bit Maybe your historical data includes car charging, you might want to filter this out using car_charging_hold (see below) Why didn't the slot actually get configured? Are you in read-only mode? Do you have the predbat_mode set to Control Charge (or Charge & Discharge)? The charge limit keeps increasing/decreasing in the charge window or is unstable Check you don't have any other automations running that adjust GivTCP settings during this time. Some people had a script that changes the reserve %, this will cause problems - please disable other automations and retry. I changed a config item but it made no difference? You might have to wait a few minutes until the next update cycle. Depending on the speed of the computer that Predbat is running on, it can take 1-5 minutes for Predbat to run through. It's all running but I'm not getting very good results You might want to tune best_soc_keep to set a minimum target battery level, e.g. I use 2.0 (for 2kWh, which is just over 20% on a 9.5kWh battery). If you set best_soc_keep too high then predbat could need to charge the battery in unfavourable import rates, so try to set it to a fairly low value, especially if you have a small battery. If you set it to zero then predbat may not charge at all, so use 0.1 as a minimum. Have a read of the energy rates configuration guide as depending on your tariff different settings maybe required Check your solar production is well calibrated (you can compare solcast vs actually in the Home Assistant energy tab or on the GivEnergy portal) Make sure your inverter max AC rate has been set correctly If you have an EV that you charge then you will want some sort of car charging sensor or use the basic car charging hold feature or your load predictions maybe unreliable Do you have a solar diverter? If so maybe you want to try using the iBoost model settings. Perhaps set up the calibration chart and let it run for 24 hours to see how things line up If your export slots are too small compared to expected check your inverter_limit is set correctly (see below) Predbat is causing warning messages in the Home Assistant Core log If you have a large input_number.predbat_forecast_plan_hours then you may see warning messages in the Home Assistant Core log about the size of the predbat.plan_html entity. This is just a warning, the entity isn't stored in the database, but you can suppress it by adding the following to your configuration.yaml: # Filter out 'message too large' warnings from Predbat logger: default: warning filters: homeassistant.components.recorder.db_schema: - \"State attributes for predbat.plan_html exceed maximum size of 16384 bytes. This can cause database performance issues; Attributes will not be stored\" Error - metric_octopus_import not set correctly or no energy rates can be read If you get this error in the Predbat log file: Check that the Octopus integration is working and that event.octopus_energy_electricity_ _current_day_rates and sensor.octopus_electricity_energy_ _current_rate are both populated by the integration. Ensure that you have followed the Octopus Integration Installation instructions , including enabling the Octopus Integration events. If you been using an older version of the Octopus integration and have upgraded to version 9 or above, then you may find that your energy sensors are named sensor.electricity_ _current_rate (i.e. no 'octopus_energy_' prefix) but the 'event' entities have the 'octopus_energy' prefix. If the 'event' and 'sensor' entities are not consistently named then Predbat will not be able to find the event entities if the sensor names don't match what's expected. To fix this, uninstall the Octopus integration, reboot Home Assistant, delete all the old Octopus sensors, and re-install the Octopus Integration . WARN: No solar data has been configured If you get this warning message in the Predbat log file: Ensure that you have installed and configured Solcast correctly Check the Solcast integration in Home Assistant is configured and enabled (go to Settings / Integrations / Solcast ) Verify the solar forecast has been populated in Home Assistant by going to Developer Tools / States, filtering on 'solcast', and checking that you can see the half-hourly solar forecasts in the Solcast entities If you can see the solcast entities but there are no forecast PV figures, try running the 'Solcast update' automation you created, and check again the solcast entities Check sensor.solcast_pv_api_limit (it's normally 10 for new Solcast accounts) meaning you can call the Solcast API 10 times a day (but if you have two solar arrays, e.g. East/West) then retrieving the forecast will count as two API calls. Compare this to sensor.solcast_pv_api_used to see how many Solcast API calls you have made today (alternatively, you can confirm how many API calls you have made today by logging into your solcast account). If you've run out of API calls you will have to wait until midnight GMT for the API count to reset. It's recommended that you don't include the Solcast forecast within your GivEnergy portal to avoid running out of API calls. Check the Solcast server API status is OK I have another problem not listed above If you are still having trouble feel free to raise a Github ticket for support","title":"FAQ"},{"location":"faq/#faq","text":"","title":"FAQ"},{"location":"faq/#ive-installed-predbat-but-i-dont-see-the-correct-entities","text":"First look at predbat.status in Home Assistant and the AppDaemon.log (which can be found in the list of log files in the System/Log area of the GUI). See if any errors are warnings are found. If you see an error it's likely something is configured wrongly, check your entity settings are correct. Make sure Solcast is installed and it's auto-updated at least a couple of times a day (see the Solcast instructions ). The default solcast sensor names maybe wrong, you might need to update the apps.yaml config to match your own names (some people don't have the solcast_ bit in their names) Did you configure AppDaemon apps_dir correctly in appdaemon.yaml ?","title":"I've installed Predbat but I don't see the correct entities"},{"location":"faq/#why-is-my-predicted-charge-higher-or-lower-than-i-might-expect","text":"Predbat is based on costing, so it will try to save you money. If you have the PV 10% option enabled it will also take into account the more worse case scenario and how often it might happen, so if the forecast is a bit unreliable it's better to charge more and not risk getting stung importing. Have you checked your energy rates for import and export are correct, maybe check the rates graph and confirm. If you do something like have export>import then Predbat will try to export as much as possible. Have you tuned Solcast to match your output accurately? Have you tuned best_soc_keep settings Do you have predicted car charging during the time period? You can also tune load_scaling and pv_scaling to adjust predictions up and down a bit Maybe your historical data includes car charging, you might want to filter this out using car_charging_hold (see below)","title":"Why is my predicted charge % higher or lower than I might expect?"},{"location":"faq/#why-didnt-the-slot-actually-get-configured","text":"Are you in read-only mode? Do you have the predbat_mode set to Control Charge (or Charge & Discharge)?","title":"Why didn't the slot actually get configured?"},{"location":"faq/#the-charge-limit-keeps-increasingdecreasing-in-the-charge-window-or-is-unstable","text":"Check you don't have any other automations running that adjust GivTCP settings during this time. Some people had a script that changes the reserve %, this will cause problems - please disable other automations and retry.","title":"The charge limit keeps increasing/decreasing in the charge window or is unstable"},{"location":"faq/#i-changed-a-config-item-but-it-made-no-difference","text":"You might have to wait a few minutes until the next update cycle. Depending on the speed of the computer that Predbat is running on, it can take 1-5 minutes for Predbat to run through.","title":"I changed a config item but it made no difference?"},{"location":"faq/#its-all-running-but-im-not-getting-very-good-results","text":"You might want to tune best_soc_keep to set a minimum target battery level, e.g. I use 2.0 (for 2kWh, which is just over 20% on a 9.5kWh battery). If you set best_soc_keep too high then predbat could need to charge the battery in unfavourable import rates, so try to set it to a fairly low value, especially if you have a small battery. If you set it to zero then predbat may not charge at all, so use 0.1 as a minimum. Have a read of the energy rates configuration guide as depending on your tariff different settings maybe required Check your solar production is well calibrated (you can compare solcast vs actually in the Home Assistant energy tab or on the GivEnergy portal) Make sure your inverter max AC rate has been set correctly If you have an EV that you charge then you will want some sort of car charging sensor or use the basic car charging hold feature or your load predictions maybe unreliable Do you have a solar diverter? If so maybe you want to try using the iBoost model settings. Perhaps set up the calibration chart and let it run for 24 hours to see how things line up If your export slots are too small compared to expected check your inverter_limit is set correctly (see below)","title":"It's all running but I'm not getting very good results"},{"location":"faq/#predbat-is-causing-warning-messages-in-the-home-assistant-core-log","text":"If you have a large input_number.predbat_forecast_plan_hours then you may see warning messages in the Home Assistant Core log about the size of the predbat.plan_html entity. This is just a warning, the entity isn't stored in the database, but you can suppress it by adding the following to your configuration.yaml: # Filter out 'message too large' warnings from Predbat logger: default: warning filters: homeassistant.components.recorder.db_schema: - \"State attributes for predbat.plan_html exceed maximum size of 16384 bytes. This can cause database performance issues; Attributes will not be stored\"","title":"Predbat is causing warning messages in the Home Assistant Core log"},{"location":"faq/#error-metric_octopus_import-not-set-correctly-or-no-energy-rates-can-be-read","text":"If you get this error in the Predbat log file: Check that the Octopus integration is working and that event.octopus_energy_electricity_ _current_day_rates and sensor.octopus_electricity_energy_ _current_rate are both populated by the integration. Ensure that you have followed the Octopus Integration Installation instructions , including enabling the Octopus Integration events. If you been using an older version of the Octopus integration and have upgraded to version 9 or above, then you may find that your energy sensors are named sensor.electricity_ _current_rate (i.e. no 'octopus_energy_' prefix) but the 'event' entities have the 'octopus_energy' prefix. If the 'event' and 'sensor' entities are not consistently named then Predbat will not be able to find the event entities if the sensor names don't match what's expected. To fix this, uninstall the Octopus integration, reboot Home Assistant, delete all the old Octopus sensors, and re-install the Octopus Integration .","title":"Error - metric_octopus_import not set correctly or no energy rates can be read"},{"location":"faq/#warn-no-solar-data-has-been-configured","text":"If you get this warning message in the Predbat log file: Ensure that you have installed and configured Solcast correctly Check the Solcast integration in Home Assistant is configured and enabled (go to Settings / Integrations / Solcast ) Verify the solar forecast has been populated in Home Assistant by going to Developer Tools / States, filtering on 'solcast', and checking that you can see the half-hourly solar forecasts in the Solcast entities If you can see the solcast entities but there are no forecast PV figures, try running the 'Solcast update' automation you created, and check again the solcast entities Check sensor.solcast_pv_api_limit (it's normally 10 for new Solcast accounts) meaning you can call the Solcast API 10 times a day (but if you have two solar arrays, e.g. East/West) then retrieving the forecast will count as two API calls. Compare this to sensor.solcast_pv_api_used to see how many Solcast API calls you have made today (alternatively, you can confirm how many API calls you have made today by logging into your solcast account). If you've run out of API calls you will have to wait until midnight GMT for the API count to reset. It's recommended that you don't include the Solcast forecast within your GivEnergy portal to avoid running out of API calls. Check the Solcast server API status is OK","title":"WARN: No solar data has been configured"},{"location":"faq/#i-have-another-problem-not-listed-above","text":"If you are still having trouble feel free to raise a Github ticket for support","title":"I have another problem not listed above"},{"location":"install/","text":"Install These instructions will take you through the process of installing and configuring Predbat for first time use. It's recommended that you watch the Video Guides before you start. A level of familiarity with the basics of Home Assistant, Add-on's, Integrations, Entities and File Editing is assumed. There are plenty of \"Home Assistant basics\" tutorials on YouTube, but if you get stuck, please read the FAQ's and if necessary raise a Github ticket for support. Inverter Control Integration install (GivTCP/SolaX-ModBus) The Integration that communicates with your inverter will be depend on the brand of inverter you have: Brand Integration Github Link GivEnergy GivTCP https://github.com/britkat1980/giv_tcp Solis SolaX ModBus https://github.com/wills106/homeassistant-solax-modbus Sofar Sofar MQTT https://github.com/cmcgerty/Sofar2mqtt Please see Other Inverters for details on how Solis, Solax and Sofar install details. Follow the installation and configuration instructions appropriate for your inverter so that Home Assistant is able to 'see' and manage your inverter. You will need at least 24 hours history in Home Assistant for Predbat to work correctly, the default is 7 days (but you configure this back to 1 day if you need to). Editing Configuration Files in Home Assistant The basic configuration for Predbat is stored in a configuration file called apps.yaml . A standard template apps.yaml file will be installed as part of the Predbat installation and you will need to edit and customise this configuration file for your own system setup. You will therefore need a method of editing configuration files within your Home Assistant environment. There are severals ways to achieve this in Home Assistant, but two of the simplest are to use either the File Editor or Studio Code Server add-on's. Whichever you use is a personal preference. File Editor is a bit simpler, Studio Code Server is more powerful but does require HACS (the Home Assistant Community Store) to be installed first. If you do not have one of these file editors already installed in Home Assistant: For Studio Code Server you will need to install HACS first if you don't currently have it installed Go to Settings / Add-ons / Add-on Store (bottom right) Scroll down the add-on store list, to find either 'File editor' or 'Studio Code Server' as appropriate, click on the add-on, click 'INSTALL' Once the editor has been installed, ensure that the 'Start on boot' option is turned on, and click 'START' to start the add-on Thereafter whenever you need to edit a configuration file in Home Assistant you can navigate to Settings / Add-on's / / 'OPEN WEB UI' If you are using the File Editor to edit Predbat's configuration files, you will need to turn off Enforce Basepath to enable you to access files in the appdaemon directory: From the File editor add-on page, click on the 'Configuration' tab to change this setting): AppDaemon-Predbat combined install The simplest way to install Predbat now is with a combined AppDaemon/Predbat add-on. This is a fork of AppDaemon which automatically includes an install of Predbat. Installing the combined AppDaemon-predbat add-on is thus simpler for new users as they do not need to install HACS, AppDaemon and Predbat as three separate installation steps. If you are already running AppDaemon then the original installation method for Predbat still exists, is still supported, and is described below in Predbat Installation into AppDaemon . To install the combined AppDaemon-predbat add-on: Go to Settings / Add-ons / Add-on Store (bottom right), click the three dots in the top right, then Repositories and type https://github.com/springfall2008/appdaemon-predbat ', click ADD, then CLOSE. In order to refresh the list of available add-on's, navigate back through Settings / Add-ons / Add-on Store, scroll down and select 'AppDaemon with Predbat' Click INSTALL and wait for the add-on to be installed Once it has finished installing, ensure that the 'Start on boot' option is turned on, then click 'START' NOTE: Throughout the rest of the Predbat documentation you will find reference to the Predbat configuration file apps.yaml and the Predbat logfile. These are located under the Home Assistant directory /addon_configs/46f69597_appdaemon-predbat which contains: predbat.log - Predbat's active logfile that reports detail of what Predbat is doing, and details of any errors apps/apps.yaml - Predbat's configuration file which will need to be customised to your system and requirements. This configuration process is described below. You can use your file editor (i.e. 'File editor' or 'Studio Code Server' add-on) to open the directory /addon_configs/46f69597_appdaemon-predbat and view these files. If you have used the AppDaemon-predbat add-on installation method you do not need to install HACS or AppDaemon so you can skip directly to Solcast install below. Predbat installation into AppDaemon This is the \"classic\" way of installing Predbat, to firstly install HACS (the Home Assistant Community Store), then install the AppDaemon add-on, and finally install Predbat from HACS to run within AppDaemon. HACS install Predbat and AppDaemon are available through the Home Assistant Community Store (HACS). You can install Predbat manually (see below) but its usually easier to install it through HACS. Install HACS if you haven't already ( https://hacs.xyz/docs/setup/download ) Enable AppDaemon in HACS: https://hacs.xyz/docs/categories/appdaemon_apps/ AppDaemon install Predbat is written in Python and runs on a continual loop (default every 5 minutes) within the AppDaemon add-on to Home Assistant. The next task therefore is to install and configure AppDaemon. Install the AppDaemon add-on https://github.com/hassio-addons/addon-appdaemon Once AppDaemon has finished installing, ensure that the 'Start on boot' option is turned on, then click 'START' You will need to edit the appdaemon.yaml configuration file for AppDaemon and so will need to have either the File Editor or Studio Code Server add-on's installed first Find the appdaemon.yaml file in the directory /addon_configs/a0d7b954_appdaemon : Add to the appdaemon.yaml configuration file: A section app_dir which should refer to the directory /homeassistant/appdaemon/apps where Predbat will be installed Ensure that the time_zone is set correctly (e.g. Europe/London) Add thread_duration_warning_threshold: 120 in the appdaemon section It's recommended you also add a logs section and specify a new logfile location so that you can see the complete logs, I set mine to /homeassistant/appdaemon/appdaemon.log and increase the logfile maximum size and number of logfile generations to capture a few days worth of logs. Example AppDaemon config in appdaemon.yaml : appdaemon: latitude: 52.379189 longitude: 4.899431 elevation: 2 time_zone: Europe/London thread_duration_warning_threshold: 120 plugins: HASS: type: hass app_dir: /homeassistant/appdaemon/apps http: url: http://homeassistant.local:5050 admin: api: hadashboard: # write log records to a file, retaining 9 versions, rather than the standard appdaemon log logs: main_log: filename: /homeassistant/appdaemon/appdaemon.log log_generations: 9 log_size: 10000000 CAUTION: If you are upgrading AppDaemon from an older version to version 0.15.2 or above you need to follow these steps to ensure Predbat continues working. These are only required if you are upgrading AppDaemon from an old version, they're not required for new installations of AppDaemon: Make sure you have access to the HA filesystem, e.g. I use the Samba add-on and connect to the drives on my Mac, but you can use ssh also. Update AppDaemon to the latest version Go into the directory /addon_configs/a0d7b954_appdaemon and edit appdaemon.yaml . You need to add app_dir (see above) to point to the old location and update your logfile location (if you have set it). You should remove the line that points to secrets.yaml (most people don't use this file) or adjust it's path to the new location ( /homeassistant/secrets.yaml ) Move the entire 'apps' directory from /addon_configs/a0d7b954_appdaemon (new location) to /config/appdaemon (the old location) Restart AppDaemon Check it has started and confirm Predbat is running correctly again. Install Predbat through HACS If you install Predbat through HACS, once installed you will get automatic updates for each new release of Predbat! In HACS, click on Automation Click on the three dots in the top right corner, choose Custom Repositories Add https://github.com/springfall2008/batpred as a custom repository of Category 'AppDaemon' and click 'Add' Click Explore and download repositories (bottom right), type 'Predbat' in the search box, select the Predbat Repository, then click 'Download' to install the Predbat app. NOTE: Throughout the rest of the Predbat documentation you will find reference to the Predbat configuration file apps.yaml and the Predbat logfile. These are located under the Home Assistant directory /config/appdaemon/ which contains: appdaemon.log - AppDaemon and Predbat's active logfile that reports detail of what Predbat is doing, and details of any errors apps/batpred/config/apps.yaml - Predbat's configuration file which will need to be customised to your system and requirements. This configuration process is described below. Predbat manual install A manual install is suitable for those running Docker type systems where HACS does not function correctly and you had to manually install AppDaemon. Note: Not recommended if you are using HACS Copy the file apps/predbat/predbat.py to the /config/appdaemon/apps/ directory in Home Assistant (or wherever you set appdaemon app_dir to) Copy apps/predbat/apps.yaml to the /config/appdaemon/apps/ directory in Home Assistant (or wherever you set appdaemon app_dir to) Edit in Home Assistant the /config/appdaemon/apps/apps.yaml file to configure Predbat If you later install with HACS then you must move the apps.yaml into /config/appdaemon/apps/predbat/config Solcast Install Predbat needs a solar forecast in order to predict solar generation and battery charging. If you don't have solar then use a file editor to comment out the following lines from the Solar forecast part of the apps.yaml configuration: pv_forecast_today: re:(sensor.(solcast_|)(pv_forecast_|)forecast_today) pv_forecast_tomorrow: re:(sensor.(solcast_|)(pv_forecast_|)forecast_tomorrow) pv_forecast_d3: re:(sensor.(solcast_|)(pv_forecast_|)forecast_(day_3|d3)) pv_forecast_d4: re:(sensor.(solcast_|)(pv_forecast_|)forecast_(day_4|d4)) If you do have solar panels its recommended to use the Solcast integration to automatically retrieve your forecast solar generation. Predbat is configured to automatically discover the Solcast forecast entities in Home Assistant. Install the Solcast integration ( https://github.com/oziee/ha-solcast-solar ), create a Solcast account , configure details of your solar arrays, and request an API key that you enter into the Solcast integration in Home Assistant. Note that Predbat does not update Solcast for you so you will need to create your own Home Assistant automation that updates the solar forecast a few times a day (e.g. dawn, dusk, and just before your nightly charge slot). Example Solcast update automation script: alias: Solcast update description: \"Update Solcast solar forecast\" trigger: - platform: time at: \"23:00:00\" - platform: time at: \"12:00:00\" - platform: time at: \"04:00:00\" condition: [] action: - service: solcast_solar.update_forecasts data: {} mode: single Manually run the automation and then make sure the Solcast integration is working in Home Assistant by going to Developer Tools / States, filtering on 'solcast', and checking that you can see the half-hourly solar forecasts in the Solcast entities. Energy Rates Predbat needs to know what your electricity import and export rates are in order to optimise battery charging and discharging to minimise your expenditure. These rates are configured in Predbat's apps.yaml configuration file. Follow the instructions in the Energy Rates document. Note: that if you are using the Octopus integration the 'sensor.octopus_xxx' and 'event.octopus_xxx' entities must have a similar pattern of names for Predbat to work correctly - see the FAQ's if they are not. Configuring Predbat You will need to use a file editor (either the File editor or Studio Code Server add-on) to edit the apps.yaml file in Home Assistant to configure Predbat - see Configuring apps.yaml . When Predbat starts up initially it will perform a sanity check of the AppDaemon configuration itself and confirm the right files are present. You will see this check in the log, should it fail a warning will be issued and predbat.status will also reflect the warning. While the above warning might not prevent Predbat from starting up, you should fix the issue ASAP as it may cause future problems. Predbat Output and Configuration Controls As described above, the basic configuration of Predbat is held in the apps.yaml configuration file. When Predbat first runs it will create a number of output and configuration control entities in Home Assistant which are used to fine-tune how Predbat operates. The entities are all prefixed predbat and can be seen (and changed) from the Settings / Devices & Services / Entities list in Home Assistant. It is recommended that you create a dashboard page with all the required entities to control Predbat and another page to display Predbat's charging and discharging plan for your battery. The Output Data section describes these points in more detail. The Home Assistant entity predbat.status contains details of what status Predbat is currently in (e.g. Idle, Charging, Error). Detailed progress messages and error logging is written to the Predbat logfile which you can view within Home Assistant using a file editor. The Predbat Configuration Guide gives an overview of the main Predbat configuration items and detail of 'standard Predbat configuration' settings for different electricity tariff types - e.g. a cheap overnight rate, multiple import rates during the day, and variable tariffs such as Agile, etc. The detailed Predbat Customisation Guide details all the Predbat configuration items (switches, input numbers, etc) in Home Assistant, and what each of them does. Ready to light the touch-paper By now you should have successfully installed and configured Predbat in AppDaemon and the other components it is dependent upon (e.g. GivTCP, Solcast, Octopus Integration). You have checked the Predbat AppDaemon log file doesn't have any errors (there is a lot of output in the logfile, this is normal). You have configured predbat's control entities, created a couple of dashboard pages to control and monitor Predbat, and are ready to start Predbat running. In order to enable Predbat you must delete the 'template: True' line in apps.yaml once you are happy with your configuration. You may initially want to set select.predbat_mode to Monitor to see how Predbat operates, e.g. by studying the Predbat Plan. Once you are happy with the plan Predbat is producing, and are ready to let Predbat start controlling your inverter, set select.predbat_mode to the correct mode of operation for your system. Updating Predbat Note that future updates to Predbat will not overwrite the apps.yaml configuration file that you have tailored to your setup. You may therefore need to manually copy across any new apps.yaml settings from the Template apps.yaml for new features. HACS Update HACS checks for updates and new releases only once a day by default, you can however force it to check again, or download a specific version by using the 'Redownload' option from the top-right three dots menu for Predbat in the HACS Automation section. NOTE: If you update Predbat through HACS you may need to restart AppDaemon as it sometimes reads the config wrongly during the update. (If this happens you will get a template configuration error in the entity predbat.status ). Go to Settings, Add-ons, AppDaemon, and click 'Restart'. Predbat built-in update Predbat can now update itself, just select the version you want from the select.predbat_update drop down menu, the latest version will be at the top of the list. Predbat will update itself and automatically restart. Alternatively, if you turn on switch.predbat_auto_update , Predbat will automatically update itself as new releases are published on Github. If you have used the Combined AppDaemon and Predbat add-on installation method then once installed and configured you should update Predbat to the latest version by using the select.predbat_update selector or by enabling the switch.predbat_auto_update . Manual update of Predbat You can go to Github and download predbat.py from the releases tab and then manually copy this file over the existing version in /config/appdaemon/apps/batpred/ manually.","title":"Install details"},{"location":"install/#install","text":"These instructions will take you through the process of installing and configuring Predbat for first time use. It's recommended that you watch the Video Guides before you start. A level of familiarity with the basics of Home Assistant, Add-on's, Integrations, Entities and File Editing is assumed. There are plenty of \"Home Assistant basics\" tutorials on YouTube, but if you get stuck, please read the FAQ's and if necessary raise a Github ticket for support.","title":"Install"},{"location":"install/#inverter-control-integration-install-givtcpsolax-modbus","text":"The Integration that communicates with your inverter will be depend on the brand of inverter you have: Brand Integration Github Link GivEnergy GivTCP https://github.com/britkat1980/giv_tcp Solis SolaX ModBus https://github.com/wills106/homeassistant-solax-modbus Sofar Sofar MQTT https://github.com/cmcgerty/Sofar2mqtt Please see Other Inverters for details on how Solis, Solax and Sofar install details. Follow the installation and configuration instructions appropriate for your inverter so that Home Assistant is able to 'see' and manage your inverter. You will need at least 24 hours history in Home Assistant for Predbat to work correctly, the default is 7 days (but you configure this back to 1 day if you need to).","title":"Inverter Control Integration install (GivTCP/SolaX-ModBus)"},{"location":"install/#editing-configuration-files-in-home-assistant","text":"The basic configuration for Predbat is stored in a configuration file called apps.yaml . A standard template apps.yaml file will be installed as part of the Predbat installation and you will need to edit and customise this configuration file for your own system setup. You will therefore need a method of editing configuration files within your Home Assistant environment. There are severals ways to achieve this in Home Assistant, but two of the simplest are to use either the File Editor or Studio Code Server add-on's. Whichever you use is a personal preference. File Editor is a bit simpler, Studio Code Server is more powerful but does require HACS (the Home Assistant Community Store) to be installed first. If you do not have one of these file editors already installed in Home Assistant: For Studio Code Server you will need to install HACS first if you don't currently have it installed Go to Settings / Add-ons / Add-on Store (bottom right) Scroll down the add-on store list, to find either 'File editor' or 'Studio Code Server' as appropriate, click on the add-on, click 'INSTALL' Once the editor has been installed, ensure that the 'Start on boot' option is turned on, and click 'START' to start the add-on Thereafter whenever you need to edit a configuration file in Home Assistant you can navigate to Settings / Add-on's / / 'OPEN WEB UI' If you are using the File Editor to edit Predbat's configuration files, you will need to turn off Enforce Basepath to enable you to access files in the appdaemon directory: From the File editor add-on page, click on the 'Configuration' tab to change this setting):","title":"Editing Configuration Files in Home Assistant"},{"location":"install/#appdaemon-predbat-combined-install","text":"The simplest way to install Predbat now is with a combined AppDaemon/Predbat add-on. This is a fork of AppDaemon which automatically includes an install of Predbat. Installing the combined AppDaemon-predbat add-on is thus simpler for new users as they do not need to install HACS, AppDaemon and Predbat as three separate installation steps. If you are already running AppDaemon then the original installation method for Predbat still exists, is still supported, and is described below in Predbat Installation into AppDaemon . To install the combined AppDaemon-predbat add-on: Go to Settings / Add-ons / Add-on Store (bottom right), click the three dots in the top right, then Repositories and type https://github.com/springfall2008/appdaemon-predbat ', click ADD, then CLOSE. In order to refresh the list of available add-on's, navigate back through Settings / Add-ons / Add-on Store, scroll down and select 'AppDaemon with Predbat' Click INSTALL and wait for the add-on to be installed Once it has finished installing, ensure that the 'Start on boot' option is turned on, then click 'START' NOTE: Throughout the rest of the Predbat documentation you will find reference to the Predbat configuration file apps.yaml and the Predbat logfile. These are located under the Home Assistant directory /addon_configs/46f69597_appdaemon-predbat which contains: predbat.log - Predbat's active logfile that reports detail of what Predbat is doing, and details of any errors apps/apps.yaml - Predbat's configuration file which will need to be customised to your system and requirements. This configuration process is described below. You can use your file editor (i.e. 'File editor' or 'Studio Code Server' add-on) to open the directory /addon_configs/46f69597_appdaemon-predbat and view these files. If you have used the AppDaemon-predbat add-on installation method you do not need to install HACS or AppDaemon so you can skip directly to Solcast install below.","title":"AppDaemon-Predbat combined install"},{"location":"install/#predbat-installation-into-appdaemon","text":"This is the \"classic\" way of installing Predbat, to firstly install HACS (the Home Assistant Community Store), then install the AppDaemon add-on, and finally install Predbat from HACS to run within AppDaemon.","title":"Predbat installation into AppDaemon"},{"location":"install/#hacs-install","text":"Predbat and AppDaemon are available through the Home Assistant Community Store (HACS). You can install Predbat manually (see below) but its usually easier to install it through HACS. Install HACS if you haven't already ( https://hacs.xyz/docs/setup/download ) Enable AppDaemon in HACS: https://hacs.xyz/docs/categories/appdaemon_apps/","title":"HACS install"},{"location":"install/#appdaemon-install","text":"Predbat is written in Python and runs on a continual loop (default every 5 minutes) within the AppDaemon add-on to Home Assistant. The next task therefore is to install and configure AppDaemon. Install the AppDaemon add-on https://github.com/hassio-addons/addon-appdaemon Once AppDaemon has finished installing, ensure that the 'Start on boot' option is turned on, then click 'START' You will need to edit the appdaemon.yaml configuration file for AppDaemon and so will need to have either the File Editor or Studio Code Server add-on's installed first Find the appdaemon.yaml file in the directory /addon_configs/a0d7b954_appdaemon : Add to the appdaemon.yaml configuration file: A section app_dir which should refer to the directory /homeassistant/appdaemon/apps where Predbat will be installed Ensure that the time_zone is set correctly (e.g. Europe/London) Add thread_duration_warning_threshold: 120 in the appdaemon section It's recommended you also add a logs section and specify a new logfile location so that you can see the complete logs, I set mine to /homeassistant/appdaemon/appdaemon.log and increase the logfile maximum size and number of logfile generations to capture a few days worth of logs. Example AppDaemon config in appdaemon.yaml : appdaemon: latitude: 52.379189 longitude: 4.899431 elevation: 2 time_zone: Europe/London thread_duration_warning_threshold: 120 plugins: HASS: type: hass app_dir: /homeassistant/appdaemon/apps http: url: http://homeassistant.local:5050 admin: api: hadashboard: # write log records to a file, retaining 9 versions, rather than the standard appdaemon log logs: main_log: filename: /homeassistant/appdaemon/appdaemon.log log_generations: 9 log_size: 10000000 CAUTION: If you are upgrading AppDaemon from an older version to version 0.15.2 or above you need to follow these steps to ensure Predbat continues working. These are only required if you are upgrading AppDaemon from an old version, they're not required for new installations of AppDaemon: Make sure you have access to the HA filesystem, e.g. I use the Samba add-on and connect to the drives on my Mac, but you can use ssh also. Update AppDaemon to the latest version Go into the directory /addon_configs/a0d7b954_appdaemon and edit appdaemon.yaml . You need to add app_dir (see above) to point to the old location and update your logfile location (if you have set it). You should remove the line that points to secrets.yaml (most people don't use this file) or adjust it's path to the new location ( /homeassistant/secrets.yaml ) Move the entire 'apps' directory from /addon_configs/a0d7b954_appdaemon (new location) to /config/appdaemon (the old location) Restart AppDaemon Check it has started and confirm Predbat is running correctly again.","title":"AppDaemon install"},{"location":"install/#install-predbat-through-hacs","text":"If you install Predbat through HACS, once installed you will get automatic updates for each new release of Predbat! In HACS, click on Automation Click on the three dots in the top right corner, choose Custom Repositories Add https://github.com/springfall2008/batpred as a custom repository of Category 'AppDaemon' and click 'Add' Click Explore and download repositories (bottom right), type 'Predbat' in the search box, select the Predbat Repository, then click 'Download' to install the Predbat app. NOTE: Throughout the rest of the Predbat documentation you will find reference to the Predbat configuration file apps.yaml and the Predbat logfile. These are located under the Home Assistant directory /config/appdaemon/ which contains: appdaemon.log - AppDaemon and Predbat's active logfile that reports detail of what Predbat is doing, and details of any errors apps/batpred/config/apps.yaml - Predbat's configuration file which will need to be customised to your system and requirements. This configuration process is described below.","title":"Install Predbat through HACS"},{"location":"install/#predbat-manual-install","text":"A manual install is suitable for those running Docker type systems where HACS does not function correctly and you had to manually install AppDaemon. Note: Not recommended if you are using HACS Copy the file apps/predbat/predbat.py to the /config/appdaemon/apps/ directory in Home Assistant (or wherever you set appdaemon app_dir to) Copy apps/predbat/apps.yaml to the /config/appdaemon/apps/ directory in Home Assistant (or wherever you set appdaemon app_dir to) Edit in Home Assistant the /config/appdaemon/apps/apps.yaml file to configure Predbat If you later install with HACS then you must move the apps.yaml into /config/appdaemon/apps/predbat/config","title":"Predbat manual install"},{"location":"install/#solcast-install","text":"Predbat needs a solar forecast in order to predict solar generation and battery charging. If you don't have solar then use a file editor to comment out the following lines from the Solar forecast part of the apps.yaml configuration: pv_forecast_today: re:(sensor.(solcast_|)(pv_forecast_|)forecast_today) pv_forecast_tomorrow: re:(sensor.(solcast_|)(pv_forecast_|)forecast_tomorrow) pv_forecast_d3: re:(sensor.(solcast_|)(pv_forecast_|)forecast_(day_3|d3)) pv_forecast_d4: re:(sensor.(solcast_|)(pv_forecast_|)forecast_(day_4|d4)) If you do have solar panels its recommended to use the Solcast integration to automatically retrieve your forecast solar generation. Predbat is configured to automatically discover the Solcast forecast entities in Home Assistant. Install the Solcast integration ( https://github.com/oziee/ha-solcast-solar ), create a Solcast account , configure details of your solar arrays, and request an API key that you enter into the Solcast integration in Home Assistant. Note that Predbat does not update Solcast for you so you will need to create your own Home Assistant automation that updates the solar forecast a few times a day (e.g. dawn, dusk, and just before your nightly charge slot). Example Solcast update automation script: alias: Solcast update description: \"Update Solcast solar forecast\" trigger: - platform: time at: \"23:00:00\" - platform: time at: \"12:00:00\" - platform: time at: \"04:00:00\" condition: [] action: - service: solcast_solar.update_forecasts data: {} mode: single Manually run the automation and then make sure the Solcast integration is working in Home Assistant by going to Developer Tools / States, filtering on 'solcast', and checking that you can see the half-hourly solar forecasts in the Solcast entities.","title":"Solcast Install"},{"location":"install/#energy-rates","text":"Predbat needs to know what your electricity import and export rates are in order to optimise battery charging and discharging to minimise your expenditure. These rates are configured in Predbat's apps.yaml configuration file. Follow the instructions in the Energy Rates document. Note: that if you are using the Octopus integration the 'sensor.octopus_xxx' and 'event.octopus_xxx' entities must have a similar pattern of names for Predbat to work correctly - see the FAQ's if they are not.","title":"Energy Rates"},{"location":"install/#configuring-predbat","text":"You will need to use a file editor (either the File editor or Studio Code Server add-on) to edit the apps.yaml file in Home Assistant to configure Predbat - see Configuring apps.yaml . When Predbat starts up initially it will perform a sanity check of the AppDaemon configuration itself and confirm the right files are present. You will see this check in the log, should it fail a warning will be issued and predbat.status will also reflect the warning. While the above warning might not prevent Predbat from starting up, you should fix the issue ASAP as it may cause future problems.","title":"Configuring Predbat"},{"location":"install/#predbat-output-and-configuration-controls","text":"As described above, the basic configuration of Predbat is held in the apps.yaml configuration file. When Predbat first runs it will create a number of output and configuration control entities in Home Assistant which are used to fine-tune how Predbat operates. The entities are all prefixed predbat and can be seen (and changed) from the Settings / Devices & Services / Entities list in Home Assistant. It is recommended that you create a dashboard page with all the required entities to control Predbat and another page to display Predbat's charging and discharging plan for your battery. The Output Data section describes these points in more detail. The Home Assistant entity predbat.status contains details of what status Predbat is currently in (e.g. Idle, Charging, Error). Detailed progress messages and error logging is written to the Predbat logfile which you can view within Home Assistant using a file editor. The Predbat Configuration Guide gives an overview of the main Predbat configuration items and detail of 'standard Predbat configuration' settings for different electricity tariff types - e.g. a cheap overnight rate, multiple import rates during the day, and variable tariffs such as Agile, etc. The detailed Predbat Customisation Guide details all the Predbat configuration items (switches, input numbers, etc) in Home Assistant, and what each of them does.","title":"Predbat Output and Configuration Controls"},{"location":"install/#ready-to-light-the-touch-paper","text":"By now you should have successfully installed and configured Predbat in AppDaemon and the other components it is dependent upon (e.g. GivTCP, Solcast, Octopus Integration). You have checked the Predbat AppDaemon log file doesn't have any errors (there is a lot of output in the logfile, this is normal). You have configured predbat's control entities, created a couple of dashboard pages to control and monitor Predbat, and are ready to start Predbat running. In order to enable Predbat you must delete the 'template: True' line in apps.yaml once you are happy with your configuration. You may initially want to set select.predbat_mode to Monitor to see how Predbat operates, e.g. by studying the Predbat Plan. Once you are happy with the plan Predbat is producing, and are ready to let Predbat start controlling your inverter, set select.predbat_mode to the correct mode of operation for your system.","title":"Ready to light the touch-paper"},{"location":"install/#updating-predbat","text":"Note that future updates to Predbat will not overwrite the apps.yaml configuration file that you have tailored to your setup. You may therefore need to manually copy across any new apps.yaml settings from the Template apps.yaml for new features.","title":"Updating Predbat"},{"location":"install/#hacs-update","text":"HACS checks for updates and new releases only once a day by default, you can however force it to check again, or download a specific version by using the 'Redownload' option from the top-right three dots menu for Predbat in the HACS Automation section. NOTE: If you update Predbat through HACS you may need to restart AppDaemon as it sometimes reads the config wrongly during the update. (If this happens you will get a template configuration error in the entity predbat.status ). Go to Settings, Add-ons, AppDaemon, and click 'Restart'.","title":"HACS Update"},{"location":"install/#predbat-built-in-update","text":"Predbat can now update itself, just select the version you want from the select.predbat_update drop down menu, the latest version will be at the top of the list. Predbat will update itself and automatically restart. Alternatively, if you turn on switch.predbat_auto_update , Predbat will automatically update itself as new releases are published on Github. If you have used the Combined AppDaemon and Predbat add-on installation method then once installed and configured you should update Predbat to the latest version by using the select.predbat_update selector or by enabling the switch.predbat_auto_update .","title":"Predbat built-in update"},{"location":"install/#manual-update-of-predbat","text":"You can go to Github and download predbat.py from the releases tab and then manually copy this file over the existing version in /config/appdaemon/apps/batpred/ manually.","title":"Manual update of Predbat"},{"location":"installation-summary/","text":"Installation summary Please see the sections below for how to achieve each step. This is just a checklist of things: Before you start, its recommended that you watch the step by step installation videos, see the video guides section for those and other videos Make sure the right inverter control module is installed and running - GivTCP or Solax install Install a file editor (either the File editor or Studio Code Server add-on) to enable you to edit configuration files if you haven't already - Editing configuration files Install Predbat and AppDaemon, either: a) Install the AppDaemon-Predbat combined add-on - AppDaemon-Predbat combined install b) Complete the separate installation steps: i) Install HACS if you haven't already - HACS install ii) Install AppDaemon if you haven't already - AppDaemon install iii) Install Predbat using HACS - Predbat install Install Solcast if you haven't already Solcast install . Create an automation to update Solcast a times a day, and check that you see the Solcast data in Home Assistant Follow the Energy Rates instructions to tell Predbat what your import and export energy rates are. If you use Octopus Energy then this includes installing the Octopus Energy integration (if you haven't already) - Octopus Energy Edit Predbat's apps.yaml configuration file to to match your system - apps.yaml settings The apps.yaml file will be in either the directory /addon_configs/46f69597_appdaemon-predbat/apps or /config/appdaemon/apps/predbat/config/ depending on which Predbat install method you used. Inverter settings match the names in GivTCP - should be automatic (but if you have 2 names you will have to edit apps.yaml) You have set the right number of inverters ( num_inverters ) Adjust your inverter_limit and export_limit as required You have your energy rates set correctly either using Octopus Energy integration or entered manually That the Solcast plugin is matching the configuration correctly - should be automatic If you have a car charging sensor you might want to add that also to help make predictions more accurate Add the Predbat entities to your dashboard - Output data Follow the Configuration Guide to set 'standard' Predbat configuration settings depending on your import and export tariffs The detailed Customisation Guide lists all Predbat's controls and settings in Home Assistant that can be tuned for your system Set up the Predbat Plan card so you can check what Predbat is planning to do - Create the Predbat Plan card Set up the Apex Charts for other views on what Predbat is doing - Creating the charts Then check Predbat is working correctly: Look at the Predbat AppDaemon log file and make sure you have no errors or warnings that are unexpected Comment out or delete the template: True line in apps.yaml when you are ready to start Predbat The predbat.status in Home Assistant should be 'Idle' (if there are any errors then they are reported here too) Start with select.predbat_mode set to 'Monitor' but remember to change it later to enable Predbat to control your inverter Look at the FAQ for help Overview of the key configuration elements:","title":"Install summary"},{"location":"installation-summary/#installation-summary","text":"Please see the sections below for how to achieve each step. This is just a checklist of things: Before you start, its recommended that you watch the step by step installation videos, see the video guides section for those and other videos Make sure the right inverter control module is installed and running - GivTCP or Solax install Install a file editor (either the File editor or Studio Code Server add-on) to enable you to edit configuration files if you haven't already - Editing configuration files Install Predbat and AppDaemon, either: a) Install the AppDaemon-Predbat combined add-on - AppDaemon-Predbat combined install b) Complete the separate installation steps: i) Install HACS if you haven't already - HACS install ii) Install AppDaemon if you haven't already - AppDaemon install iii) Install Predbat using HACS - Predbat install Install Solcast if you haven't already Solcast install . Create an automation to update Solcast a times a day, and check that you see the Solcast data in Home Assistant Follow the Energy Rates instructions to tell Predbat what your import and export energy rates are. If you use Octopus Energy then this includes installing the Octopus Energy integration (if you haven't already) - Octopus Energy Edit Predbat's apps.yaml configuration file to to match your system - apps.yaml settings The apps.yaml file will be in either the directory /addon_configs/46f69597_appdaemon-predbat/apps or /config/appdaemon/apps/predbat/config/ depending on which Predbat install method you used. Inverter settings match the names in GivTCP - should be automatic (but if you have 2 names you will have to edit apps.yaml) You have set the right number of inverters ( num_inverters ) Adjust your inverter_limit and export_limit as required You have your energy rates set correctly either using Octopus Energy integration or entered manually That the Solcast plugin is matching the configuration correctly - should be automatic If you have a car charging sensor you might want to add that also to help make predictions more accurate Add the Predbat entities to your dashboard - Output data Follow the Configuration Guide to set 'standard' Predbat configuration settings depending on your import and export tariffs The detailed Customisation Guide lists all Predbat's controls and settings in Home Assistant that can be tuned for your system Set up the Predbat Plan card so you can check what Predbat is planning to do - Create the Predbat Plan card Set up the Apex Charts for other views on what Predbat is doing - Creating the charts Then check Predbat is working correctly: Look at the Predbat AppDaemon log file and make sure you have no errors or warnings that are unexpected Comment out or delete the template: True line in apps.yaml when you are ready to start Predbat The predbat.status in Home Assistant should be 'Idle' (if there are any errors then they are reported here too) Start with select.predbat_mode set to 'Monitor' but remember to change it later to enable Predbat to control your inverter Look at the FAQ for help Overview of the key configuration elements:","title":"Installation summary"},{"location":"other-inverters/","text":"Other Inverters PredBat was originally written for GivEnergy inverters using the GivTCP integration but this is now being extended to other models: Solis Hybrid inverters Solax Modbus integration Solax Gen4 inverters Solax Modbus integration in Modbus Power Control Mode Sofar inverters Sofar MQTT integration SolarEdge inverters - Work in progress, please contribute Note that support for all these inverters is in various stages of development. Please expect things to fail and report them as Issues on Github. Please also ensure you have set up enhanced logging in AppDaemon as described here. Solis Inverters To run PredBat with Solis hybrid inverters, follow the following steps: Install PredBat as per the Installation Summary Ensure that you have the Solax Modbus integration running. There are a number of entities which this integration disables by default that you will need to enable via the Home Assistant GUI: Name Description sensor.solisx_rtc Real Time Clock sensor.solisx_battery_power Battery Power Instead of apps.yaml use ginlong_solis.yaml from this Repo as your starting template. The majority of settings should be correct but please check. You will need to un-comment the template line to enable it. Save it to the config/appdaemon/apps/predbat/config folder. Ensure that the inverter is set Control Mode 35 - on the Solax integration this is Timed Charge/Discharge . If you want to use the Reserve functionality within PredBat you will need to select Backup/Reserve (code 51) instead but be aware that this is not fully tested. In due course these mode settings will be incorporated into the code. Solax Inverters Please see this ticket in Github for ongoing discussion: https://github.com/springfall2008/batpred/issues/259 Sofar Inverters For this integration the key elements are: Hardware - sofar2mqtt EPS board - Relatively easy to solder and flash, or can be bought pre-made. Software - Sofar MQTT integration - MQTT integration Home Assistant configuration - sofar_inverter.yaml package (in templates directory) with the MQTT sensors. This is the default with a couple of additional inputs to support battery capacity. This should be installed in Home Assistant. Predbat configuration - sofar.yaml template for Predbat (in templates directory). This file should be copied to apps.yaml This integration has various limitations, it can charge and discharge the battery but does not have finer control over reserve and target SOC% Note: You will need to change the min reserve in Home Assistant to match your minimum battery level. Please see this ticket in Github for ongoing discussions: https://github.com/springfall2008/batpred/issues/395","title":"Other Inverters"},{"location":"other-inverters/#other-inverters","text":"PredBat was originally written for GivEnergy inverters using the GivTCP integration but this is now being extended to other models: Solis Hybrid inverters Solax Modbus integration Solax Gen4 inverters Solax Modbus integration in Modbus Power Control Mode Sofar inverters Sofar MQTT integration SolarEdge inverters - Work in progress, please contribute Note that support for all these inverters is in various stages of development. Please expect things to fail and report them as Issues on Github. Please also ensure you have set up enhanced logging in AppDaemon as described here.","title":"Other Inverters"},{"location":"other-inverters/#solis-inverters","text":"To run PredBat with Solis hybrid inverters, follow the following steps: Install PredBat as per the Installation Summary Ensure that you have the Solax Modbus integration running. There are a number of entities which this integration disables by default that you will need to enable via the Home Assistant GUI: Name Description sensor.solisx_rtc Real Time Clock sensor.solisx_battery_power Battery Power Instead of apps.yaml use ginlong_solis.yaml from this Repo as your starting template. The majority of settings should be correct but please check. You will need to un-comment the template line to enable it. Save it to the config/appdaemon/apps/predbat/config folder. Ensure that the inverter is set Control Mode 35 - on the Solax integration this is Timed Charge/Discharge . If you want to use the Reserve functionality within PredBat you will need to select Backup/Reserve (code 51) instead but be aware that this is not fully tested. In due course these mode settings will be incorporated into the code.","title":"Solis Inverters"},{"location":"other-inverters/#solax-inverters","text":"Please see this ticket in Github for ongoing discussion: https://github.com/springfall2008/batpred/issues/259","title":"Solax Inverters"},{"location":"other-inverters/#sofar-inverters","text":"For this integration the key elements are: Hardware - sofar2mqtt EPS board - Relatively easy to solder and flash, or can be bought pre-made. Software - Sofar MQTT integration - MQTT integration Home Assistant configuration - sofar_inverter.yaml package (in templates directory) with the MQTT sensors. This is the default with a couple of additional inputs to support battery capacity. This should be installed in Home Assistant. Predbat configuration - sofar.yaml template for Predbat (in templates directory). This file should be copied to apps.yaml This integration has various limitations, it can charge and discharge the battery but does not have finer control over reserve and target SOC% Note: You will need to change the min reserve in Home Assistant to match your minimum battery level. Please see this ticket in Github for ongoing discussions: https://github.com/springfall2008/batpred/issues/395","title":"Sofar Inverters"},{"location":"output-data/","text":"Output data Displaying output data Each Predbat config item has an input_number or switch associated with it, you can find an auto-generated dashboard for your configuration in your AppDaemon configuration area under the filename predbat_dashboard.yaml . You will need to open that file in a Home Assistant file editor and copy the contents into a new dashboard page. You can also create a dashboard page using dynamic-entities-card.yaml for a dynamically created list of all Predbat entities which groups the entities by type and is collapsed by default to prevent screen clutter. Requires lovelace-collapsable-cards ( https://github.com/RossMcMillan92/lovelace-collapsable-cards ) and lovelace-auto-entities ( https://github.com/thomasloven/lovelace-auto-entities ) to be installed via HACS as well as the stock vertical stack card. Credit @DJBenson for the code. The Predbat Plan card is very useful for seeing the plan that Predbat has created - Create the Predbat Plan card . A set of Apex Charts can also be created to see graphically what Predbat plans to do - Creating the charts . Basic status predbat.status - Gives the current status & errors and logs any changes that Predbat makes to your inverter Baseline data What your battery is expected to do with no changes made by Predbat: predbat.battery_hours_left - The number of hours left until your home battery is predicted to run out (stops at the maximum prediction time) predbat.charge_limit - The current charge limit used for the scenario in % predbat.charge_limit_kw - The current charge limit used for the scenario in kwH predbat.duration - The duration of the prediction maximum in hours predbat.load_energy - Predicted load energy in kWh predbat.pv_energy - Predicted PV energy in kWh predbat.export_energy - Predicted export energy in kWh predbat.import_energy - Predicted import energy in kWh predbat.import_energy_battery - Predicted import energy to charge your home battery in kWh predbat.import_energy_house - Predicted import energy not provided by your home battery (flat battery or above maximum discharge rate) predbat.soc_kw - Predicted state of charge (in kWh) at the end of the prediction, not very useful in itself, but holds all minute by minute prediction data (in attributes) which can be charted with Apex Charts (or similar) predbat.soc_min_kwh - The minimum battery level during the time period in kWh predbat.metric - Predicted cost metric for the next simulated period (in pence). Also contains data for charting cost in attributes. predbat.battery_power - Predicted battery power per minute, for charting predbat.battery_cycle - Predicted battery cycle in kWh (total kWh processed) predbat.pv_power - Predicted PV power per minute, for charting predbat.grid_power - Predicted Grid power per minute, for charting predbat.car_soc - Predicted car battery % PV 10% baseline data The calculated baseline results under PV 10% scenario: predbat.soc_kw_base10 - As soc_kw but using the 10% solar forecast, also holds minute by minute data (in attributes) to be charted predbat.base10_pv_energy - Predicted PV 10% energy in kWh predbat.base10_metric - Predicted cost for PV 10% predbat.base10_export_energy- Predicted export energy for PV 10% predbat.base10_load_energy - Predicted load energy for PV 10% predbat.base10_import_energy- Predicted import energy for PV 10% Best When calculate_best is enabled a second set of entities are created for the simulation based on the best battery charge percentage: predbat.best_battery_hours_left - Number of hours left under best plan predbat.best_export_energy - Predicted exports under best plan predbat_best_import_energy - Predicted imports under best plan predbat_best_load - Predicted best load energy predbat.best_pv_energy - Predicted Best PV energy in kWh predbat_best_import_energy_battery - Predicted imports to the battery under best SOC setting predbat_best_import_energy_house - Predicted imports to the house under best SOC setting predbat_soc_kw_best - Predicted best final state of charge (in kWh), holds minute by minute prediction data (in attributes) to be charted predbat.soc_kw_best_h1 - Single data point for the predicted state of charge in 1 hours time (useful for calibration charts, predicted vs actual) predbat.soc_kw_best_h8 - Single data point for the predicted state of charge in 8 hours time (useful for calibration charts, predicted vs actual) predbat.soc_kw_best_h12 - Single data point for the predicted state of charge in 12 hours time (useful for calibration charts, predicted vs actual) predbat_best_metric - The predicted cost if the proposed SOC % charge target is selected. Also contains data for charting cost in attributes. predbat.best_charge_limit - Predicted best battery charge limit in percent predbat.best_charge_limit_kw - Predicted best battery charge limit in kwH predbat.best_discharge_limit - Predicted best battery discharge limit in percent (will be 0% when discharging or 100% when not) predbat.best_discharge_limit_kw - Predicted best battery discharge limit in kwH predbat.battery_power_best - Predicted best battery power per minute, for charting predbat.battery_cycle_best - Predicted best battery cycle in kWh (total kWh processed) predbat.pv_power_best - Predicted best PV power per minute, for charting predbat.grid_power - Predicted best Grid power per minute, for charting predbat.car_soc_best - Predicated car battery % in best plan predbat.iboost_best - Gives the predicted energy going into the iBoost - for charter input_number.iboost_today - Gives the amount of energy modelled into the diverter today, resets at 11:30pm each night. Increments in the day. Best PV 10% The calculated best results under PV 10% scenario: predbat.soc_kw_best10 - As soc_kw_best but using the 10% solar forecast, also holds minute by minute data (in attributes) to be charted predbat.best10_pv_energy - Predicted best PV 10% energy in kWh predbat.best10_metric - Predicted best cost for PV 10% predbat.best10_export_energy- Predicted best export energy for PV 10% predbat.best10_load_energy - Predicted best load energy for PV 10% predbat.best10_import_energy- Predicted best import energy for PV 10% Energy rate data Low import rate entities predbat.low_rate_cost - The lowest import rate cost in P predbat.low_rate_start - Start time of the next low import rate predbat.low_rate_end - End time of the next low import rate predbat.low_rate_cost_2, predbat.low_rate_start_2, predbat.low_rate_end_2 - The following low import rate slot binary_sensor.predbat_low_rate_slot - A sensor that indicates which there is a low energy rate slot active High export rate entities predbat.high_export_rate_cost - The highest rate cost in P predbat.high_export_rate_start - Start time of the next high export rate predbat.high_export_rate_end - End time of the next high export rate predbat.high_export_rate_cost_2, predbat.high_export_rate_start_2, predbat.high_export_rate_end_2 - The following high export rate slot binary_sensor.predbat_high_export_rate_slot - A sensor that indicates which there is a high export rate slot active Other rate entities predbat.rates - The current energy rates in P (also can be charted) predbat.rates_export - The current energy export rates in P (also be be charted) predbat.cost_today - The total cost of energy so far today (since midnight) predbat.car_soc - The expected charge level of your car at the end of the simulation. Can also be charted. predbat.car_soc_best - The expected charge level of your car at the end of the simulation using the proposed SOC%/Window. Can also be charted. Car data binary_sensor.predbat_car_charging_slot - A binary sensor suggesting when to charge your car (if the car planning is enabled) Sample Predbat data out dashboard Predbat Logfile Predbat writes detailed logging, status and progress activity information to a logfile as it runs and so this file should be checked if predbat.status reports an error, or if you want to verify that Predbat is running OK. There is a lot of output in the logfile, this is normal! Depending upon whether you have used the combined AppDaemon/Predbat add-on installation method or the HACS, Appdaemon add-on then Predbat installation method , the logfile will be held in one of two directories in Home Assistant: /addon_configs/46f69597_appdaemon-predbat/predbat.log if you used the combined AppDaemon/Predbat add-on installation method or /homeassistant/appdaemon/appdaemon.log if you used the HACS, AppDaemon add-on then Predbat installation method You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) to view Predbat's logfile - see editing configuration files within Home Assistant if you need to install an editor. Automated monitoring that Predbat and GivTCP are running OK With GivTCP and Predbat performing an important function, managing your battery charging and discharging to best reduce your electricity bills, you may find these automations useful to monitor that GivTCP and Predbat are running OK, and if not, to raise an alert on your mobile device. GivTCP activity monitor This automation will raise an alert if any of the following occur: The inverter goes offline for more than 30 minutes No last_updated_time received from the inverter for more than 30 minutes The battery goes offline to the inverter for more than 30 minutes The script will need to be customised for your inverter id, battery id and mobile details, and can be extended for multiple inverters and batteries. alias: GivTCP activity monitor description: Alert when communications to GivTCP have ceased for 30 minutes trigger: - platform: state entity_id: sensor.givtcp__last_updated_time to: null for: minutes: 30 id: no-givtcp-update variables: inv_id: inverter - platform: state entity_id: - sensor.givtcp__status from: online for: minutes: 30 id: no-givtcp-update variables: inv_id: inverter - platform: state entity_id: - sensor.givtcp__battery_cells to: unknown for: minutes: 30 id: battery-unavailable variables: batt_id: action: - condition: trigger id: - no-givtcp-update - service: notify.mobile_app_ data: title: GivTCP communication issue message: | {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE: No GivTCP update received from {{ inv_id }} for the past 30 minutes. data: visibility: public persistent: true push: sound: name: default critical: 1 volume: 0.8 sticky: true color: red - condition: trigger id: - battery-unavailable - service: notify.mobile_app_ data: title: GivTCP communication issue message: | {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE: Battery {{ batt_id }} offline to GivTCP for the past 30 minutes. data: visibility: public persistent: true push: sound: name: default critical: 1 volume: 0.8 sticky: true color: red mode: single Predbat error monitor This automation will raise an alert if Predbat's status turns to ERROR for more than 10 minutes. The script will need to be customised for your mobile details. alias: predbat error monitor description: Alert when Predbat has raised an exception trigger: - platform: state entity_id: - predbat.status to: \"ERROR: Exception raised\" for: minutes: 10 - platform: template value_template: \"{{ 'ERROR' in states('predbat.status') }}\" for: minutes: 10 action: - service: notify.mobile_app_ data: title: Predbat status issue message: | {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE: predbat status is {{ states('predbat.status') }} data: visibility: public persistent: true push: sound: name: default critical: 1 volume: 0.8 sticky: true color: red mode: single An error alert looks like this:","title":"Output data"},{"location":"output-data/#output-data","text":"","title":"Output data"},{"location":"output-data/#displaying-output-data","text":"Each Predbat config item has an input_number or switch associated with it, you can find an auto-generated dashboard for your configuration in your AppDaemon configuration area under the filename predbat_dashboard.yaml . You will need to open that file in a Home Assistant file editor and copy the contents into a new dashboard page. You can also create a dashboard page using dynamic-entities-card.yaml for a dynamically created list of all Predbat entities which groups the entities by type and is collapsed by default to prevent screen clutter. Requires lovelace-collapsable-cards ( https://github.com/RossMcMillan92/lovelace-collapsable-cards ) and lovelace-auto-entities ( https://github.com/thomasloven/lovelace-auto-entities ) to be installed via HACS as well as the stock vertical stack card. Credit @DJBenson for the code. The Predbat Plan card is very useful for seeing the plan that Predbat has created - Create the Predbat Plan card . A set of Apex Charts can also be created to see graphically what Predbat plans to do - Creating the charts .","title":"Displaying output data"},{"location":"output-data/#basic-status","text":"predbat.status - Gives the current status & errors and logs any changes that Predbat makes to your inverter","title":"Basic status"},{"location":"output-data/#baseline-data","text":"What your battery is expected to do with no changes made by Predbat: predbat.battery_hours_left - The number of hours left until your home battery is predicted to run out (stops at the maximum prediction time) predbat.charge_limit - The current charge limit used for the scenario in % predbat.charge_limit_kw - The current charge limit used for the scenario in kwH predbat.duration - The duration of the prediction maximum in hours predbat.load_energy - Predicted load energy in kWh predbat.pv_energy - Predicted PV energy in kWh predbat.export_energy - Predicted export energy in kWh predbat.import_energy - Predicted import energy in kWh predbat.import_energy_battery - Predicted import energy to charge your home battery in kWh predbat.import_energy_house - Predicted import energy not provided by your home battery (flat battery or above maximum discharge rate) predbat.soc_kw - Predicted state of charge (in kWh) at the end of the prediction, not very useful in itself, but holds all minute by minute prediction data (in attributes) which can be charted with Apex Charts (or similar) predbat.soc_min_kwh - The minimum battery level during the time period in kWh predbat.metric - Predicted cost metric for the next simulated period (in pence). Also contains data for charting cost in attributes. predbat.battery_power - Predicted battery power per minute, for charting predbat.battery_cycle - Predicted battery cycle in kWh (total kWh processed) predbat.pv_power - Predicted PV power per minute, for charting predbat.grid_power - Predicted Grid power per minute, for charting predbat.car_soc - Predicted car battery %","title":"Baseline data"},{"location":"output-data/#pv-10-baseline-data","text":"The calculated baseline results under PV 10% scenario: predbat.soc_kw_base10 - As soc_kw but using the 10% solar forecast, also holds minute by minute data (in attributes) to be charted predbat.base10_pv_energy - Predicted PV 10% energy in kWh predbat.base10_metric - Predicted cost for PV 10% predbat.base10_export_energy- Predicted export energy for PV 10% predbat.base10_load_energy - Predicted load energy for PV 10% predbat.base10_import_energy- Predicted import energy for PV 10%","title":"PV 10% baseline data"},{"location":"output-data/#best","text":"When calculate_best is enabled a second set of entities are created for the simulation based on the best battery charge percentage: predbat.best_battery_hours_left - Number of hours left under best plan predbat.best_export_energy - Predicted exports under best plan predbat_best_import_energy - Predicted imports under best plan predbat_best_load - Predicted best load energy predbat.best_pv_energy - Predicted Best PV energy in kWh predbat_best_import_energy_battery - Predicted imports to the battery under best SOC setting predbat_best_import_energy_house - Predicted imports to the house under best SOC setting predbat_soc_kw_best - Predicted best final state of charge (in kWh), holds minute by minute prediction data (in attributes) to be charted predbat.soc_kw_best_h1 - Single data point for the predicted state of charge in 1 hours time (useful for calibration charts, predicted vs actual) predbat.soc_kw_best_h8 - Single data point for the predicted state of charge in 8 hours time (useful for calibration charts, predicted vs actual) predbat.soc_kw_best_h12 - Single data point for the predicted state of charge in 12 hours time (useful for calibration charts, predicted vs actual) predbat_best_metric - The predicted cost if the proposed SOC % charge target is selected. Also contains data for charting cost in attributes. predbat.best_charge_limit - Predicted best battery charge limit in percent predbat.best_charge_limit_kw - Predicted best battery charge limit in kwH predbat.best_discharge_limit - Predicted best battery discharge limit in percent (will be 0% when discharging or 100% when not) predbat.best_discharge_limit_kw - Predicted best battery discharge limit in kwH predbat.battery_power_best - Predicted best battery power per minute, for charting predbat.battery_cycle_best - Predicted best battery cycle in kWh (total kWh processed) predbat.pv_power_best - Predicted best PV power per minute, for charting predbat.grid_power - Predicted best Grid power per minute, for charting predbat.car_soc_best - Predicated car battery % in best plan predbat.iboost_best - Gives the predicted energy going into the iBoost - for charter input_number.iboost_today - Gives the amount of energy modelled into the diverter today, resets at 11:30pm each night. Increments in the day.","title":"Best"},{"location":"output-data/#best-pv-10","text":"The calculated best results under PV 10% scenario: predbat.soc_kw_best10 - As soc_kw_best but using the 10% solar forecast, also holds minute by minute data (in attributes) to be charted predbat.best10_pv_energy - Predicted best PV 10% energy in kWh predbat.best10_metric - Predicted best cost for PV 10% predbat.best10_export_energy- Predicted best export energy for PV 10% predbat.best10_load_energy - Predicted best load energy for PV 10% predbat.best10_import_energy- Predicted best import energy for PV 10%","title":"Best PV 10%"},{"location":"output-data/#energy-rate-data","text":"","title":"Energy rate data"},{"location":"output-data/#low-import-rate-entities","text":"predbat.low_rate_cost - The lowest import rate cost in P predbat.low_rate_start - Start time of the next low import rate predbat.low_rate_end - End time of the next low import rate predbat.low_rate_cost_2, predbat.low_rate_start_2, predbat.low_rate_end_2 - The following low import rate slot binary_sensor.predbat_low_rate_slot - A sensor that indicates which there is a low energy rate slot active","title":"Low import rate entities"},{"location":"output-data/#high-export-rate-entities","text":"predbat.high_export_rate_cost - The highest rate cost in P predbat.high_export_rate_start - Start time of the next high export rate predbat.high_export_rate_end - End time of the next high export rate predbat.high_export_rate_cost_2, predbat.high_export_rate_start_2, predbat.high_export_rate_end_2 - The following high export rate slot binary_sensor.predbat_high_export_rate_slot - A sensor that indicates which there is a high export rate slot active","title":"High export rate entities"},{"location":"output-data/#other-rate-entities","text":"predbat.rates - The current energy rates in P (also can be charted) predbat.rates_export - The current energy export rates in P (also be be charted) predbat.cost_today - The total cost of energy so far today (since midnight) predbat.car_soc - The expected charge level of your car at the end of the simulation. Can also be charted. predbat.car_soc_best - The expected charge level of your car at the end of the simulation using the proposed SOC%/Window. Can also be charted.","title":"Other rate entities"},{"location":"output-data/#car-data","text":"binary_sensor.predbat_car_charging_slot - A binary sensor suggesting when to charge your car (if the car planning is enabled)","title":"Car data"},{"location":"output-data/#sample-predbat-data-out-dashboard","text":"","title":"Sample Predbat data out dashboard"},{"location":"output-data/#predbat-logfile","text":"Predbat writes detailed logging, status and progress activity information to a logfile as it runs and so this file should be checked if predbat.status reports an error, or if you want to verify that Predbat is running OK. There is a lot of output in the logfile, this is normal! Depending upon whether you have used the combined AppDaemon/Predbat add-on installation method or the HACS, Appdaemon add-on then Predbat installation method , the logfile will be held in one of two directories in Home Assistant: /addon_configs/46f69597_appdaemon-predbat/predbat.log if you used the combined AppDaemon/Predbat add-on installation method or /homeassistant/appdaemon/appdaemon.log if you used the HACS, AppDaemon add-on then Predbat installation method You will need to use a file editor within Home Assistant (e.g. either the File editor or Studio Code Server add-on's) to view Predbat's logfile - see editing configuration files within Home Assistant if you need to install an editor.","title":"Predbat Logfile"},{"location":"output-data/#automated-monitoring-that-predbat-and-givtcp-are-running-ok","text":"With GivTCP and Predbat performing an important function, managing your battery charging and discharging to best reduce your electricity bills, you may find these automations useful to monitor that GivTCP and Predbat are running OK, and if not, to raise an alert on your mobile device.","title":"Automated monitoring that Predbat and GivTCP are running OK"},{"location":"output-data/#givtcp-activity-monitor","text":"This automation will raise an alert if any of the following occur: The inverter goes offline for more than 30 minutes No last_updated_time received from the inverter for more than 30 minutes The battery goes offline to the inverter for more than 30 minutes The script will need to be customised for your inverter id, battery id and mobile details, and can be extended for multiple inverters and batteries. alias: GivTCP activity monitor description: Alert when communications to GivTCP have ceased for 30 minutes trigger: - platform: state entity_id: sensor.givtcp__last_updated_time to: null for: minutes: 30 id: no-givtcp-update variables: inv_id: inverter - platform: state entity_id: - sensor.givtcp__status from: online for: minutes: 30 id: no-givtcp-update variables: inv_id: inverter - platform: state entity_id: - sensor.givtcp__battery_cells to: unknown for: minutes: 30 id: battery-unavailable variables: batt_id: action: - condition: trigger id: - no-givtcp-update - service: notify.mobile_app_ data: title: GivTCP communication issue message: | {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE: No GivTCP update received from {{ inv_id }} for the past 30 minutes. data: visibility: public persistent: true push: sound: name: default critical: 1 volume: 0.8 sticky: true color: red - condition: trigger id: - battery-unavailable - service: notify.mobile_app_ data: title: GivTCP communication issue message: | {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE: Battery {{ batt_id }} offline to GivTCP for the past 30 minutes. data: visibility: public persistent: true push: sound: name: default critical: 1 volume: 0.8 sticky: true color: red mode: single","title":"GivTCP activity monitor"},{"location":"output-data/#predbat-error-monitor","text":"This automation will raise an alert if Predbat's status turns to ERROR for more than 10 minutes. The script will need to be customised for your mobile details. alias: predbat error monitor description: Alert when Predbat has raised an exception trigger: - platform: state entity_id: - predbat.status to: \"ERROR: Exception raised\" for: minutes: 10 - platform: template value_template: \"{{ 'ERROR' in states('predbat.status') }}\" for: minutes: 10 action: - service: notify.mobile_app_ data: title: Predbat status issue message: | {{ now().timestamp() | timestamp_custom('%-d %b %H:%M') }} ISSUE: predbat status is {{ states('predbat.status') }} data: visibility: public persistent: true push: sound: name: default critical: 1 volume: 0.8 sticky: true color: red mode: single An error alert looks like this:","title":"Predbat error monitor"},{"location":"predbat-plan-card/","text":"Predbat Plan card Predbat can create its own plan card which can be added to your HA dashboard. First install html-template-card in HACS (from the Frontend list), it will already be available to add, but for reference the repository can be found here: https://github.com/PiotrMachowski/Home-Assistant-Lovelace-HTML-Jinja2-Template-card Next create a new card as follows: type: custom:html-template-card title: Predbat plan ignore_line_breaks: true content: | {{ state_attr('predbat.plan_html', 'html') }} You should see something like this:","title":"Predbat Plan card"},{"location":"predbat-plan-card/#predbat-plan-card","text":"Predbat can create its own plan card which can be added to your HA dashboard. First install html-template-card in HACS (from the Frontend list), it will already be available to add, but for reference the repository can be found here: https://github.com/PiotrMachowski/Home-Assistant-Lovelace-HTML-Jinja2-Template-card Next create a new card as follows: type: custom:html-template-card title: Predbat plan ignore_line_breaks: true content: | {{ state_attr('predbat.plan_html', 'html') }} You should see something like this:","title":"Predbat Plan card"},{"location":"todo-list/","text":"To-do list See Github issues","title":"To-do list"},{"location":"todo-list/#to-do-list","text":"See Github issues","title":"To-do list"},{"location":"video-guides/","text":"Video Guides All the video guides are now available on my YouTube channel: Springfall2008 Basic installation Playlist of Predbat installation videos Setting Up HomeAssistant Basics, File Editor, SSH, HACS, Octopus, eWelink Installing MQTT and GivTCP on Home Assistant Predbat installation - Predbat, Solcast, Dashboard, Charts and Plans Configuration of apps.yaml Configuration of Predbat inside Home Assistant Understanding historical data Understanding the charts How to understand Predbat plans AppDaemon log files Other configuration videos Playlist of other Predbat configuration videos AppDaemon Configuration process Fixing the new version so HACS still works (after updating AppDaemon) Multiple cars Octopus Energy plugin >v9.0.0 Features Playlist of Predbat feature videos Intelligent Octopus car charging Octopus Saving Sessions How to update Predbat Predbat mode and read-only mode Energy Tariffs Playlist of Tariff configuration videos Intelligent Octopus import + Agile export Intelligent Octopus import + Fixed export Octopus Agile import + Agile export Octopus Flux","title":"Video Guides"},{"location":"video-guides/#video-guides","text":"All the video guides are now available on my YouTube channel: Springfall2008","title":"Video Guides"},{"location":"video-guides/#basic-installation","text":"Playlist of Predbat installation videos Setting Up HomeAssistant Basics, File Editor, SSH, HACS, Octopus, eWelink Installing MQTT and GivTCP on Home Assistant Predbat installation - Predbat, Solcast, Dashboard, Charts and Plans Configuration of apps.yaml Configuration of Predbat inside Home Assistant Understanding historical data Understanding the charts How to understand Predbat plans AppDaemon log files","title":"Basic installation"},{"location":"video-guides/#other-configuration-videos","text":"Playlist of other Predbat configuration videos AppDaemon Configuration process Fixing the new version so HACS still works (after updating AppDaemon) Multiple cars Octopus Energy plugin >v9.0.0","title":"Other configuration videos"},{"location":"video-guides/#features","text":"Playlist of Predbat feature videos Intelligent Octopus car charging Octopus Saving Sessions How to update Predbat Predbat mode and read-only mode","title":"Features"},{"location":"video-guides/#energy-tariffs","text":"Playlist of Tariff configuration videos Intelligent Octopus import + Agile export Intelligent Octopus import + Fixed export Octopus Agile import + Agile export Octopus Flux","title":"Energy Tariffs"},{"location":"what-does-predbat-do/","text":"What does Predbat do? Predbat is a home battery automation program. It automatically runs every 5 minutes and will update its prediction for the home battery levels for the next period, up to a maximum of 48 hours ahead. Predbat will automatically decide when to charge and discharge your battery to achieve the best (lowest) cost spend within the parameters you have set. It uses the solar production forecast from Solcast combined with your historical energy usage to make this prediction. The output is a prediction of the battery levels, charging slots, discharging slots, costs and import and export amounts. Costs are based on energy pricing data, either manually configured (e.g. 7p from 11pm-4pm and 35p otherwise) or by using the Octopus Energy integration Both import and export rates are supported. Intelligent Octopus is also supported and takes into account allocated charging slots. The solar forecast used is the central scenario from Solcast (50%) with a configurable weighting towards the more pessimistic (10%) scenario. The charging and discharging controls are automatically programmed into the inverter. Automatic planning of export slots is also supported, when enabled Predbat can start a forced discharge of the battery if the export rates are high and you have spare capacity. Historical load data is used to predict your consumption, optionally car charging load can be filtered out of this data. Predbat can be configured to manage the charging of your EV and take into account its load on the house during these periods. Multiple inverter support is included but depends on all inverters running in lockstep. Terminology Basic terminology SOC - State of Charge - the % or kWh level of charge of your battery Target SOC - The target level that the battery is being charged to, e.g. we target 100% SOC means the battery is being charged to full Load - The energy your home is using to power your equipment e.g. oven, lights or electric car charging Grid - Your electric supply outside the house Import - Electricity drawn from the grid to be used in the home or to charge the battery Export - Electricity from your home from the battery or solar which is sent to the grid. PV - Solar power that is generated in your home Inverter - The box that converts DC energy from solar or from your battery into AC power for your home and the grid. The inverter also converts AC power from the grid into DC to charge a battery. Hybrid inverter - An inverter that can charge a battery from solar directly using DC power as well as charging it from AC power from the grid. AC Coupled - A battery that comes with it's own inverter and is always charged or discharged with AC (using an internal inverter) Slot - A period of time where Predbat performs an action e.g. charging. In Predbat everything is a multiple of 5 minutes. Charge slots are always in multiples of 30 minutes and align to a 30-minute boundary to match the way energy rates are allocated. Discharge slots can be any multiple of 5 minutes and always finish on a 30-minute boundary. Predbat modes When you first install Predbat it will be in 'Monitor' mode. You can configure Predbat's mode of operation using the drop down menu in select.predbat_mode . You will find a full description of Predbat Modes in the Customisation Guide. Once you are ready for Predbat to take control move this setting to one of the active control modes. Predbat status The current Predbat status is reported in the Home Assistant entity predbat.status : Idle - This is the default, the load will be covered by solar and/or battery. Excess solar will charge the battery or be exported if the battery is full. This is described as 'ECO' Mode for GivEnergy inverters but other inverters use different terminology. Charging - The battery charges from the grid and the grid also covers any load. Solar power will also be used to charge the battery. Freeze charging - The current battery level is held and the grid/solar covers any load. Solar power will also be used to charge the battery. Hold charging - A type of charge where the target SOC % is the same as the current SOC %, effectively the same as a charge freeze (but without being explicitly selected). No Charge - A charge where the target SOC % is lower than the current battery SOC level so there will be no charging unless the usage is unexpectedly high. Discharging - The battery is being force-discharged. The house load will be covered by the battery and any excess is exported to the grid. Any solar generated will be exported. Freeze discharging - The battery is covering the load but charging is disabled, thus any solar generated will be exported. Error - There is a configuration error or other problem, you should check the Predbat AppDaemon log file for more details.","title":"What does Predbat do?"},{"location":"what-does-predbat-do/#what-does-predbat-do","text":"Predbat is a home battery automation program. It automatically runs every 5 minutes and will update its prediction for the home battery levels for the next period, up to a maximum of 48 hours ahead. Predbat will automatically decide when to charge and discharge your battery to achieve the best (lowest) cost spend within the parameters you have set. It uses the solar production forecast from Solcast combined with your historical energy usage to make this prediction. The output is a prediction of the battery levels, charging slots, discharging slots, costs and import and export amounts. Costs are based on energy pricing data, either manually configured (e.g. 7p from 11pm-4pm and 35p otherwise) or by using the Octopus Energy integration Both import and export rates are supported. Intelligent Octopus is also supported and takes into account allocated charging slots. The solar forecast used is the central scenario from Solcast (50%) with a configurable weighting towards the more pessimistic (10%) scenario. The charging and discharging controls are automatically programmed into the inverter. Automatic planning of export slots is also supported, when enabled Predbat can start a forced discharge of the battery if the export rates are high and you have spare capacity. Historical load data is used to predict your consumption, optionally car charging load can be filtered out of this data. Predbat can be configured to manage the charging of your EV and take into account its load on the house during these periods. Multiple inverter support is included but depends on all inverters running in lockstep.","title":"What does Predbat do?"},{"location":"what-does-predbat-do/#terminology","text":"","title":"Terminology"},{"location":"what-does-predbat-do/#basic-terminology","text":"SOC - State of Charge - the % or kWh level of charge of your battery Target SOC - The target level that the battery is being charged to, e.g. we target 100% SOC means the battery is being charged to full Load - The energy your home is using to power your equipment e.g. oven, lights or electric car charging Grid - Your electric supply outside the house Import - Electricity drawn from the grid to be used in the home or to charge the battery Export - Electricity from your home from the battery or solar which is sent to the grid. PV - Solar power that is generated in your home Inverter - The box that converts DC energy from solar or from your battery into AC power for your home and the grid. The inverter also converts AC power from the grid into DC to charge a battery. Hybrid inverter - An inverter that can charge a battery from solar directly using DC power as well as charging it from AC power from the grid. AC Coupled - A battery that comes with it's own inverter and is always charged or discharged with AC (using an internal inverter) Slot - A period of time where Predbat performs an action e.g. charging. In Predbat everything is a multiple of 5 minutes. Charge slots are always in multiples of 30 minutes and align to a 30-minute boundary to match the way energy rates are allocated. Discharge slots can be any multiple of 5 minutes and always finish on a 30-minute boundary.","title":"Basic terminology"},{"location":"what-does-predbat-do/#predbat-modes","text":"When you first install Predbat it will be in 'Monitor' mode. You can configure Predbat's mode of operation using the drop down menu in select.predbat_mode . You will find a full description of Predbat Modes in the Customisation Guide. Once you are ready for Predbat to take control move this setting to one of the active control modes.","title":"Predbat modes"},{"location":"what-does-predbat-do/#predbat-status","text":"The current Predbat status is reported in the Home Assistant entity predbat.status : Idle - This is the default, the load will be covered by solar and/or battery. Excess solar will charge the battery or be exported if the battery is full. This is described as 'ECO' Mode for GivEnergy inverters but other inverters use different terminology. Charging - The battery charges from the grid and the grid also covers any load. Solar power will also be used to charge the battery. Freeze charging - The current battery level is held and the grid/solar covers any load. Solar power will also be used to charge the battery. Hold charging - A type of charge where the target SOC % is the same as the current SOC %, effectively the same as a charge freeze (but without being explicitly selected). No Charge - A charge where the target SOC % is lower than the current battery SOC level so there will be no charging unless the usage is unexpectedly high. Discharging - The battery is being force-discharged. The house load will be covered by the battery and any excess is exported to the grid. Any solar generated will be exported. Freeze discharging - The battery is covering the load but charging is disabled, thus any solar generated will be exported. Error - There is a configuration error or other problem, you should check the Predbat AppDaemon log file for more details.","title":"Predbat status"}]} \ No newline at end of file diff --git a/search/worker.js b/search/worker.js new file mode 100644 index 000000000..8628dbce9 --- /dev/null +++ b/search/worker.js @@ -0,0 +1,133 @@ +var base_path = 'function' === typeof importScripts ? '.' : '/search/'; +var allowSearch = false; +var index; +var documents = {}; +var lang = ['en']; +var data; + +function getScript(script, callback) { + console.log('Loading script: ' + script); + $.getScript(base_path + script).done(function () { + callback(); + }).fail(function (jqxhr, settings, exception) { + console.log('Error: ' + exception); + }); +} + +function getScriptsInOrder(scripts, callback) { + if (scripts.length === 0) { + callback(); + return; + } + getScript(scripts[0], function() { + getScriptsInOrder(scripts.slice(1), callback); + }); +} + +function loadScripts(urls, callback) { + if( 'function' === typeof importScripts ) { + importScripts.apply(null, urls); + callback(); + } else { + getScriptsInOrder(urls, callback); + } +} + +function onJSONLoaded () { + data = JSON.parse(this.responseText); + var scriptsToLoad = ['lunr.js']; + if (data.config && data.config.lang && data.config.lang.length) { + lang = data.config.lang; + } + if (lang.length > 1 || lang[0] !== "en") { + scriptsToLoad.push('lunr.stemmer.support.js'); + if (lang.length > 1) { + scriptsToLoad.push('lunr.multi.js'); + } + if (lang.includes("ja") || lang.includes("jp")) { + scriptsToLoad.push('tinyseg.js'); + } + for (var i=0; i < lang.length; i++) { + if (lang[i] != 'en') { + scriptsToLoad.push(['lunr', lang[i], 'js'].join('.')); + } + } + } + loadScripts(scriptsToLoad, onScriptsLoaded); +} + +function onScriptsLoaded () { + console.log('All search scripts loaded, building Lunr index...'); + if (data.config && data.config.separator && data.config.separator.length) { + lunr.tokenizer.separator = new RegExp(data.config.separator); + } + + if (data.index) { + index = lunr.Index.load(data.index); + data.docs.forEach(function (doc) { + documents[doc.location] = doc; + }); + console.log('Lunr pre-built index loaded, search ready'); + } else { + index = lunr(function () { + if (lang.length === 1 && lang[0] !== "en" && lunr[lang[0]]) { + this.use(lunr[lang[0]]); + } else if (lang.length > 1) { + this.use(lunr.multiLanguage.apply(null, lang)); // spread operator not supported in all browsers: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Spread_operator#Browser_compatibility + } + this.field('title'); + this.field('text'); + this.ref('location'); + + for (var i=0; i < data.docs.length; i++) { + var doc = data.docs[i]; + this.add(doc); + documents[doc.location] = doc; + } + }); + console.log('Lunr index built, search ready'); + } + allowSearch = true; + postMessage({config: data.config}); + postMessage({allowSearch: allowSearch}); +} + +function init () { + var oReq = new XMLHttpRequest(); + oReq.addEventListener("load", onJSONLoaded); + var index_path = base_path + '/search_index.json'; + if( 'function' === typeof importScripts ){ + index_path = 'search_index.json'; + } + oReq.open("GET", index_path); + oReq.send(); +} + +function search (query) { + if (!allowSearch) { + console.error('Assets for search still loading'); + return; + } + + var resultDocuments = []; + var results = index.search(query); + for (var i=0; i < results.length; i++){ + var result = results[i]; + doc = documents[result.ref]; + doc.summary = doc.text.substring(0, 200); + resultDocuments.push(doc); + } + return resultDocuments; +} + +if( 'function' === typeof importScripts ) { + onmessage = function (e) { + if (e.data.init) { + init(); + } else if (e.data.query) { + postMessage({ results: search(e.data.query) }); + } else { + console.error("Worker - Unrecognized message: " + e); + } + }; +} diff --git a/sitemap.xml b/sitemap.xml new file mode 100644 index 000000000..0f8724efd --- /dev/null +++ b/sitemap.xml @@ -0,0 +1,3 @@ + + + \ No newline at end of file diff --git a/sitemap.xml.gz b/sitemap.xml.gz new file mode 100644 index 000000000..cff03b027 Binary files /dev/null and b/sitemap.xml.gz differ diff --git a/todo-list/index.html b/todo-list/index.html new file mode 100644 index 000000000..1615acc83 --- /dev/null +++ b/todo-list/index.html @@ -0,0 +1,166 @@ + + + + + + + + To-do list - Predbat Documentation + + + + + + + + + + + + + +
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What does Predbat do?

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Predbat is a home battery automation program.

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It automatically runs every 5 minutes and will update its prediction for the home battery levels for the next period, up to a maximum of 48 hours ahead. +Predbat will automatically decide when to charge and discharge your battery to achieve the best (lowest) cost spend within the parameters you have set. +It uses the solar production forecast from Solcast combined with your historical +energy usage to make this prediction.

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  • The output is a prediction of the battery levels, charging slots, discharging slots, costs and import and export amounts.
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  • Costs are based on energy pricing data, either manually configured (e.g. 7p from 11pm-4pm and 35p otherwise) or by using the Octopus Energy integration
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    • Both import and export rates are supported.
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    • Intelligent Octopus is also supported and takes into account allocated charging slots.
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  • The solar forecast used is the central scenario from Solcast (50%) with a configurable weighting towards the more pessimistic (10%) scenario.
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  • The charging and discharging controls are automatically programmed into the inverter.
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  • Automatic planning of export slots is also supported, when enabled Predbat can start a forced discharge of the battery if the export rates are high and you have spare capacity.
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  • Historical load data is used to predict your consumption, optionally car charging load can be filtered out of this data.
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  • Predbat can be configured to manage the charging of your EV and take into account its load on the house during these periods.
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  • Multiple inverter support is included but depends on all inverters running in lockstep.
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Terminology

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Basic terminology

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  • SOC - State of Charge - the % or kWh level of charge of your battery
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  • Target SOC - The target level that the battery is being charged to, e.g. we target 100% SOC means the battery is being charged to full
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  • Load - The energy your home is using to power your equipment e.g. oven, lights or electric car charging
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  • Grid - Your electric supply outside the house
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  • Import - Electricity drawn from the grid to be used in the home or to charge the battery
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  • Export - Electricity from your home from the battery or solar which is sent to the grid.
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  • PV - Solar power that is generated in your home
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  • Inverter - The box that converts DC energy from solar or from your battery into AC power for your home and the grid. +The inverter also converts AC power from the grid into DC to charge a battery.
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  • Hybrid inverter - An inverter that can charge a battery from solar directly using DC power as well as charging it from AC power from the grid.
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  • AC Coupled - A battery that comes with it's own inverter and is always charged or discharged with AC (using an internal inverter)
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  • Slot - A period of time where Predbat performs an action e.g. charging. In Predbat everything is a multiple of 5 minutes.
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    • Charge slots are always in multiples of 30 minutes and align to a 30-minute boundary to match the way energy rates are allocated.
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    • Discharge slots can be any multiple of 5 minutes and always finish on a 30-minute boundary.
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Predbat modes

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When you first install Predbat it will be in 'Monitor' mode.

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You can configure Predbat's mode of operation using the drop down menu in select.predbat_mode. +You will find a full description of Predbat Modes in the Customisation Guide.

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Once you are ready for Predbat to take control move this setting to one of the active control modes.

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Predbat status

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The current Predbat status is reported in the Home Assistant entity predbat.status:

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    Idle - This is the default, the load will be covered by solar and/or battery. Excess solar will charge the battery or be +exported if the battery is full. This is described as 'ECO' Mode for GivEnergy inverters but other inverters use different terminology.

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    Charging - The battery charges from the grid and the grid also covers any load. Solar power will also be used to charge the battery.

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  • Freeze charging - The current battery level is held and the grid/solar covers any load. Solar power will also be used to charge the battery.
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  • Hold charging - A type of charge where the target SOC % is the same as the current SOC %, effectively the same as a charge freeze (but without being explicitly selected).
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    No Charge - A charge where the target SOC % is lower than the current battery SOC level so there will be no charging unless the usage is unexpectedly high.

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    Discharging - The battery is being force-discharged. The house load will be covered by the battery and any excess is exported to the grid. Any solar generated will be exported.

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    Freeze discharging - The battery is covering the load but charging is disabled, thus any solar generated will be exported.

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    Error - There is a configuration error or other problem, you should check the Predbat AppDaemon log file for more details.

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