Pandapower-An Open-Source Python Tool for Convenient Modeling, Analysis, and Optimization of Electric Power Systems

• Published in: IEEE transactions on power systems 2018-11, Vol.33 (6), p.6510-6521
• Main Authors: Thurner, Leon, Scheidler, Alexander, Schafer, Florian, Menke, Jan-Hendrik, Dollichon, Julian, Meier, Friederike, Meinecke, Steffen, Braun, Martin
• Format: Article
• Language: English
• Subjects: automated network analysis; Automation; Data structures; Electric power systems; Equivalent circuits; graph search; IEC60909; Industry standards; Load flow; Mathematical model; Mathematical models; Newton optimal power flow; Newton-Raphson method; open source; Open source software; optimal power flow; Optimization; Parameters; power flow; power system analysis; Power system analysis computing; Power systems; Python; short circuit; Short circuits; Software development tools; State estimation; Switches; Switching theory; Systems analysis
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2018.2829021

Pandapower is a Python-based BSD-licensed power system analysis tool aimed at automation of static and quasi-static analysis and optimization of balanced power systems. It provides power flow, optimal power flow, state estimation, topological graph searches, and short-circuit calculations according to IEC 60909. pandapower includes a Newton-Raphson power flow solver formerly based on pypower , which has been accelerated with just-in-time compilation. Additional enhancements to the solver include the capability to model constant current loads, grids with multiple reference nodes, and a connectivity check. The pandapower network model is based on electric elements, such as lines, two- and three-winding transformers, or ideal switches. All elements can be defined with nameplate parameters and are internally processed with equivalent circuit models, which have been validated against industry standard software tools. The tabular data structure used to define networks is based on the Python library pandas, which allows comfortable handling of input and output parameters. The implementation in Python makes pandapower easy to use and allows comfortable extension with third-party libraries. pandapower has been successfully applied in several grid studies as well as for educational purposes. A comprehensive publicly available case study demonstrates a possible application of pandapower in an automated time-series calculation.