Overview
PyPSA-GB is an open, peer-reviewed model of the Great Britain power system, built at the University of Edinburgh on the PyPSA framework. It represents the GB generation fleet, demand, and transmission network over a range of resolutions, for both past and future years.
PyPSA-GB draws on a variety of open data sources including the Renewable Energy Planning Datacase and Digest of UK Energy Statistics for model assets, as well as the NESO Future Energy Scenarios and Electricity Ten Year Statement for future developments.
Models
We build and host a reduced set of PyPSA-GB files on this page for easy and free access, in Convexity .db format and in PyPSA .nc format. For the full workflow and set of configurations, you can build the model from scratch using github.com/andrewlyden/PyPSA-GB. We host two network configurations:
- Wholesale — the 32-bus network solved copper-plate, for a single GB day-ahead clearing price and the national generation mix.
- Nodal — the large-scale transmission network solved with NESO aggregate-boundary limits, for locational dispatch and renewable curtailment.
Each of these is published as hindcasts for 2023 and 2024, with the wholesale model validated against real prices, and the nodal model validated against real dispatch and curtailment. We also host a model solved for 2030 in the FES Holistic Transition scenario.
We do not currently host versions of the custom day-ahead market-clearing routine in PyPSA-GB, or its custom Balancing Mechanism implementation, providing default least-cost optimisation solves.
For a quick demo of the network, you can open the Demo PyPSA-GB in Convexity in your browser. This provides a one-week slice of the full 2024 model, solving in about two minutes in the cloud.
Scenario
The free .db ships with a what-if scenario alongside the base case: a gas-price shock that raises every gas generator's marginal cost by 50%. Switch to it in Convexity and re-solve to watch CCGT and OCGT plant cede the merit order to cheaper generation, with day-ahead prices climbing in the hours gas would have set them. Only the changed generator costs are stored — everything else is shared with the base case.
Map
Each .db carries a United Kingdom border layer (GeoJSON from Natural Earth), drawn in the Convexity network tree and on the map, so the GB network sits in geographic context. Both the .db and the solved .nc are free downloads (sign-in).
Sources
PyPSA-GB is the work of its upstream authors; please cite them:
- Code: github.com/andrewlyden/PyPSA-GB
- Documentation: pypsa-gb.readthedocs.io
- Paper: Lyden et al., PyPSA-GB: An open-source model of Great Britain's power system — ScienceDirect
- Author: Dr Andrew Lyden, University of Edinburgh
License: MIT (upstream). Published in the Convexity Modelverse with credit to the original authors.