pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systems (1709.06743v3)

Abstract: 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.

• The paper presents pandapower as a novel tool that simplifies power system modeling and analysis using an element-based approach.
• It employs advanced power flow algorithms with just-in-time compilation to achieve superior performance over legacy methods in medium-to-large networks.
• Its flexible design and user-friendly interface support grid studies and educational applications, paving the way for future enhancements.

Overview of pandapower: An Open Source Python Tool

This paper presents pandapower, a Python-based, open-source tool designed for the modeling, analysis, and optimization of electric power systems. As power systems evolve toward distributed generation and automation, tools like pandapower offer a necessary solution by providing a high degree of automation, ease of use, and transparency for users and researchers alike.

Key Features and Enhancements

pandapower addresses the need for a symmetric distribution system analysis tool that automates static and quasi-static analyses. It provides several key functionalities, including power flow calculations, optimal power flow, state estimation, graph searches, and short circuit calculations in adherence to IEC 60909 standards. Notably, its power flow solver has been enhanced from pypower’s Newton-Raphson method through the use of just-in-time compilation, enabling better performance.

Significant numerical results in the paper include a speed comparison with matpower and pypower, demonstrating pandapower's superior performance in medium-to-large network scenarios. This performance, combined with its comprehensive model library, showcases pandapower as a robust tool for both educational and research purposes.

Architectural Design and Data Structure

At the architectural level, pandapower employs an element-based model (EBM) as opposed to the traditional bus-branch model (BBM). This allows more convenient modeling using nameplate parameters familiar to industry professionals. The library relies on the pandas data structure, enabling efficient handling and manipulation of network data and results.

The EBM approach allows users to model complex elements such as three-winding transformers and ideal switches diligently. This versatility is essential for simulating realistic power systems, especially when coupled with advanced analysis functionalities.

Application in Grid Studies and Educational Use

The tool's application has been proven in various grid studies, highlighting its practical implications. For instance, a detailed case paper demonstrates its utility in active grid operation using a quasi-static time series simulation. This showcases pandapower’s ability to adapt to grid reconfigurations and handle constraints such as maintaining balanced radial systems, all with minimal coding effort.

Additionally, its user-friendly interface and extensive documentation make it an excellent resource for educational environments, facilitating learning and experimentation with contemporary power system analysis.

Future Developments and Implications

Looking ahead, pandapower’s development roadmap includes plans for unbalanced power flow implementations and graphical user interfaces. Its evolution is poised to further address complex analysis requirements, enhancing the capabilities of researchers and engineers in simulation and analysis tasks.

In conclusion, pandapower stands out due to its flexibility, comprehensive element library, and enhanced calculation speed. It serves as a powerful tool for enhancing our understanding and optimization of modern electric power systems. With continued development, pandapower is expected to support more advanced simulations and offer additional capabilities to meet the demands of evolving power infrastructures.