PyPSA: Python for Power System Analysis

TLDR

PyPSA is a free toolbox that simulates and optimises modern electrical power systems over multiple periods, bridging traditional steady‑state power flow tools and full multi‑period energy system models. This paper describes PyPSA’s basic functionality, including full power flow equations and multi‑period optimisation, and highlights its extensibility and scalability to large networks and long time series. PyPSA models conventional generators with unit commitment, variable renewables, storage, sector coupling, and mixed AC/DC networks, and demonstrates its functionality on German and European transmission datasets from SciGRID and GridKit. Funding: This research was conducted under the CoNDyNet project, supported by the German Federal Ministry of Education and Research (grant 03SF0472C), and the authors bear sole responsibility for the content.

Abstract

Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and optimising modern electrical power systems over multiple periods. PyPSA includes models for conventional generators with unit commitment, variable renewable generation, storage units, coupling to other energy sectors, and mixed alternating and direct current networks. It is designed to be easily extensible and to scale well with large networks and long time series. In this paper the basic functionality of PyPSA is described, including the formulation of the full power flow equations and the multi-period optimisation of operation and investment with linear power flow equations. PyPSA is positioned in the existing free software landscape as a bridge between traditional power flow analysis tools for steady-state analysis and full multi-period energy system models. The functionality is demonstrated on two open datasets of the transmission system in Germany (based on SciGRID) and Europe (based on GridKit). Funding statement: This research was conducted as part of the CoNDyNet project, which is supported by the German Federal Ministry of Education and Research under grant no. 03SF0472C. The responsibility for the contents lies solely with the authors