What is this?

This software aims to be a complete platform for power systems research and simulation. Watch the video and check out the manual

Standalone setup

You can install GridCal as a separated standalone program without having to bother about setting up python.

GridCal for windows x64

GridCal for linux x64

Python package installation

GridCal is multiplatform and it will work in Linux, Windows and OSX.

The recommended way to install GridCal if you have a python distribution already is to open a console and type:

pip install GridCal (Windows)

pip3 install GridCal (Linux / OSX)

*You must have Python 3.5 or higher installed to work with the GUI

Check out the video on how to install Python and GridCal on Windows 10.

Manual package installation

Sometimes pip does not download the lattest version for some reason. In those cases, go to https://pypi.python.org/pypi/GridCal/ and download the lattest GridCal file: GridCal-x.xx.tar.gz.

From a console install the file manually:

Windows: pip install GridCal-x.xx.tar.gz

OSX/Linux: pip3 install GridCal-x.xx.tar.gz

Installation from GitHub

To install the development version of GridCal that lives under UnderDevelopment, open a console and type:

python3 -m pip install -e 'git+git://github.com/SanPen/GridCal.git#egg=GridCal&subdirectory=UnderDevelopment'

Installing GridCal from GitHub, pip can still freeze the version using a commit hash:

python -m pip install -e 'git+git://github.com/SanPen/GridCal.git@5c4dcb96998ae882412b5fee977cf0cff7a40d3c#egg=GridCal&subdirectory=UnderDevelopment'

Here 5c4dcb96998ae882412b5fee977cf0cff7a40d3c is the git version.

Run with user interface

From a Python console:

from GridCal.ExecuteGridCal import run
run()

Or directly from the shell:

• (Windows, with python 3.5 or higher)

  python -c "from GridCal.ExecuteGridCal import run; run()"

• (Linux/OSX)

  python3 -c "from GridCal.ExecuteGridCal import run; run()"

The GUI should pop up.

Using GridCal as a library

You can use the calculation engine directly or from other applications:

from GridCal.grid.CalculationEngine import *

Then you can create the grid objects and access the simulation objects as demonstrated in the test scripts in the test folder.

GridCal/UnderDevelopment/GridCal/tests/

I use the engine to get the admittance matrix, power injections, etc. and then do research without having to worry about getting those vectors and matrices right since they are well calculated in the engine.

Example:

from GridCal.grid.CalculationEngine import *

# Declare a multi-circuit object
grid = MultiCircuit()

# Load the IEEE30 bus grid in the circuit object
grid.load_file('IEEE30.xlsx')

# Compile the grid
grid.compile()

# Pick the circuit 0, if there are no islands all the grid elements are in this object.
# Each island holds its own calculation objects
circuit = grid.circuits[0]

# Print some useful computed vectors and matrices
print('\nYbus:\n', circuit.power_flow_input.Ybus.todense())
print('\nYseries:\n', circuit.power_flow_input.Yseries.todense())
print('\nYshunt:\n', circuit.power_flow_input.Yshunt)
print('\nSbus:\n', circuit.power_flow_input.Sbus)
print('\nIbus:\n', circuit.power_flow_input.Ibus)
print('\nVbus:\n', circuit.power_flow_input.Vbus)
print('\ntypes:\n', circuit.power_flow_input.types)
print('\npq:\n', circuit.power_flow_input.pq)
print('\npv:\n', circuit.power_flow_input.pv)
print('\nvd:\n', circuit.power_flow_input.ref)

The main logic is to store the grid elements information in objects, and then "compile the objects" to get efficient arrays that represent the grid for calculation.

The compilation detects the islands formed in the grid and treats each island as a different power system. Then the results are merged back into single multi-island vectors of results.

All the engine objects and calculations can be accessed through the embedded python console in the GUI.

Features overview

It is pure Python, It works for Windows, Linux and OSX.

Some of the features you'll find already are:

• Compatible with other formats:

  • Import
    • CIM (Common Information Model v16)
    • PSS/e RAW versions 30, 32 and 33.
    • Matpower (might not be fully compatible, notify me if not).
    • DigSilent .DGS (not be fully compatible: Only positive sequence and devices like loads, generators, etc.)
  • Export
    • Excel (normal GridCal format)
    • Custom JSON
    • CIM (Common Information Model v16)

• Power flow:

  • Newton Raphson Iwamoto (robust Newton Raphson).
  • Fast Decoupled Power Flow
  • Levenberg-Marquardt (Works very well with large ill-conditioned grids)
  • Holomorphic Embedding Power Flow (Unicorn under investigation...)
  • DC approximation.
  • Linear AC approximation.

• DC Optimal power flow

• Time series with profiles in all the objects physical magnitudes.

• Bifurcation point with predictor-corrector Newton-Raphson.

• Monte Carlo simulation based on the input profiles. (Stochastic power flow)

• Latin Hypercube Sampling based on the input profiles.

• Blackout cascading in simulation and step by step mode.

• Three-phase short circuit.

• Includes the Z-I-P load model, this means that the power flows can handle both power and current.

• The ability to handle island grids in all the simulation modes.

• Profile editor and importer from Excel and CSV.

Visit the Wiki to learn more and get started.

Send feedback and requests to [email protected].