PyPSA Welcome to the
PyPSA Community!
PyPSA stands for Python for Power System Analysis.
Free. Open-Source. Batteries included.
Features
PyPSA Framework
An open-source Python framework for optimising modern power systems with conventional generators, renewable energy, storage, and multi-sector coupling - designed for researchers and planners.
Model short-term market dispatch with unit commitment, renewables, storage, multi-carrier conversion, and more.
Optimize power flow in AC-DC networks using linearized KVL/KCL constraints with optional loss approximations.
Ensure system reliability by accounting for line outage contingencies under N-1 conditions.
Plan long-term infrastructure investments for generation, storage, transmission, and conversion with continuous or discrete options.
Co-optimize multi-period investments to design energy transition pathways with perfect foresight planning.
Solve large-scale problems sequentially with myopic foresight and dynamic updates across time horizons.
Two-stage stochastic programming for uncertainty handling with weighted scenarios and separate investment-dispatch decisions.
Explore alternative system designs with similar costs to understand trade-offs and decision flexibility.
Built-in support for COâ‚‚ limits, subsidies, resource limits, expansion limits, and growth constraints.
Impose custom objectives, variables and constraints using Linopy for specialized requirements.
Support for wide range of LP, MILP, and QP solvers from open-source to commercial solutions.
Ecosystem
Framework and Tools
PyPSA and its complementary tools and initiatives
A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series
Python for Power System Analysis - the core framework for simulating and optimising modern power systems
Community-driven initiative mapping the world's electrical grids to accelerate the energy transition worldwide
A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series
Python for Power System Analysis - the core framework for simulating and optimising modern power systems
Community-driven initiative mapping the world's electrical grids to accelerate the energy transition worldwide
Implementations
PyPSA Models
Open Energy System Models built with PyPSA
A flexible Python-based open optimisation model to study energy system futures around the world
High resolution, sector-coupled model of the German Energy System
A flexible Python-based open optimisation model to study energy system futures around the world
High resolution, sector-coupled model of the German Energy System
Contributors
Community
The people who power PyPSA
Last updated: Nov 24, 2025
References
Related Research
Numerous research publications are built on the PyPSA environment. Here we highlight some of them. For an extended list, have a look at the up-to-date Google Scholar query.
PyPSA: Python for power system analysis
T Brown, J Hörsch, D Schlachtberger - arXiv preprint arXiv:1707.09913, 2017 - arxiv.org
2017 · 895 citations
Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system
T Brown, D Schlachtberger, A Kies, S Schramm… - Energy, 2018 - Elsevier
2018 · 890 citations
On the history and future of 100% renewable energy systems research
C Breyer, S Khalili, D Bogdanov, M Ram… - IEEe …, 2022 - ieeexplore.ieee.org
2022 · 568 citations
Classification and challenges of bottom-up energy system models-A review
MG Prina, G Manzolini, D Moser, B Nastasi… - … and Sustainable Energy …, 2020 - Elsevier
2020 · 488 citations
Trends in tools and approaches for modelling the energy transition
M Chang, JZ Thellufsen, B Zakeri, B Pickering… - Applied Energy, 2021 - Elsevier
2021 · 429 citations
Last updated: Nov 24, 2025
