PFPy provides a wrapper around PowerFactory's Python API with additional features in pfpy.pf.
Furthermore, pfpy.models provides a high-level access to PowerFactory models, e.g. via:
model.simulate()model.linearize()model.set_params()
It has been developed at the Division of Electric Power and Energy Systems, KTH Royal Institute of Technology.
The code has been tested with PowerFactory 2019 and PowerFactory 2020.
The module can be installed using pip as follows:
pip install pfpy
All the requirements except powerfactory API should be installed. Note that $PYTHONPATH needs to point to the PowerFactory Python API to be able to use it. It is located in %POWERFACTORYPATH/Python/%version. The code has been tested with Python 3.7 and 3.8.
The PowerFactory model used in all of the examples is located in ./examples/data/models/PFPY_DEMO.pfd
The simulation of the aforementioned model is demonstrated in the simulation example. The model contains a controllable voltage source at the PCC. CSV files are generated that are replayed at the PCC, simulation is executed and the results are plotted.
The same model is linearized as seen from the PCC in the following Jupyter notebook. When compared to the linearization in PowerFacory, this code, in addition to the A matrix, provides also B,C, and D matrices.
Automatically generated documentation from docstrings can be found here.
Parts of this code were inspired by the following book: Francisco Gonzalez-Longatt, José Luis Rueda Torres, Advanced Smart Grid Functionalities Based on PowerFactory, Springer, 2017