PyPSA-FES offers a complete data pipeline and optimisation backbone to model any year between 2023 and 2050 of Great Britain's energy transition both for an optimisic transition scenario Leading the Way, and a pessimistic version Falling Short. For the chosen scenario and year, the model dynamically retrieves parameters on generation, transmission and storage capacities, demand and emission targets from national grid ESO's Future Energy Scenarios, and runs a full year of hourly investment and operational optimisation for a 16-zonal network. Neighbouring countries are modelled as single nodes, to realistically capture opportunities for electricity trading via interconnectors.
Our model builds on the highly popular PyPSA-Eur model, which has been adapted to focus on the electricity sector in the United Kingdom.
For details on installation, tutorial, and a deeper overview of model assumptions we refer to the documentation.
Additionally, the model includes three types of domestic demand flexibility, that can be switched on or off
- Demand Flexibility Service; individual households shifting their demand in time.
- Smart Heat Pumps storing heat provided by heat pumps in homes' thermal inertia.
- Smart Charging Electric Vehicles and Vehicle-to-Grid according to centrally optimised schedules.
While only considering electricity demand, the model aims to assume a role that fits with the transition of the larger multi-sector energy system:
- Increased electricity demand due to electrification of heat and transport.
- Negative emissions using carbon capture and storage, simulating carbon trading with hard to abate sectors.
- Competition for biomass supply with other sectors.
The model is an adaption of the PyPSA-Eur, a sector-coupled european energy model, developed at TU Berlin, built on the underlying Python modelling library PyPSA. For more details on the underlying PyPSA-Eur model, we refer to the model documentation or related research for instance PyPSA-Eur: An Open Optimisation Model of the European Transmission System, 2018, arXiv:1806.01613.
The model is governed through a snakemake workflow. Please see the documentation for installation instructions and other useful information about the snakemake workflow. The model is designed to be imported into the open toolbox PyPSA.
We strongly welcome anyone interested in contributing to this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on GitHub.
- For questions and comments please contact Lukas Franken via [email protected].
- For bugs and feature requests, please use the PyPSA-FES Github Issues page.
The code in this repository is released as free software under the MIT License, see LICENSE.txt. However, different licenses and terms of use may apply to the various input data.