This repository includes an exemplary case study that demonstrates the capabilities of pandapower. The case study showcases some pandapower functionality and is also used in a reference paper for pandapower, which has been accepted for publication in IEEE Transaction on Power Systems. A preprint of this paper is available on arXiv. Please acknowledge the usage of pandapower by citing the Paper as follows:
- L. Thurner, A. Scheidler, F. Schäfer et al., “pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systems,” IEEE Transaction on Power Systems (to be published), 2018.
You can use the following BibTex entry:
@ARTICLE{pandapower.2018,
author = {{Thurner}, L. and {Scheidler}, A. and {Sch{\"a}fer}, F. and {Menke}, J.-H. and {Dollichon}, J. and {Meier}, F. and {Meinecke}, S. and {Braun}, M.},
journal={IEEE Transactions on Power Systems},
title={pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systems},
year={2018},
doi={10.1109/TPWRS.2018.2829021}
}
The case study consists of three parts, which are available in interactive jupyter notebooks:
- Definition of a 10kV ring main grid in radial operation (grid.ipynb)
- Analysis of all possible switching states in the grid to analyse feasible switch positions considering radiality and short-circuit constraints (switch_evaluation.ipynb)
- Time series simulation for one day optimising switching states and transformer taps considering active power losses, line loading, transformer loading and voltage constraints (time_series_simulation.ipynb)
The case study works with pandapower 1.4.3.
git clone https://github.com/e2nIEE/pandapower-paper
It's recommended to use a virtualenv, it's up to you!
pip install -r requirements.txt
jupyter notebook