Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 6 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org, zenodo.org
  • Committers with academic emails
    11 of 54 committers (20.4%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.4%) to scientific vocabulary

Keywords from Contributors

energy-system-model energy-system snakemake-workflow sector-coupling pypsa power-systems great-britain energy-transition energy-model demand-flexibility
Last synced: 7 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: LukasFrankenQ
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: dev
  • Size: 105 MB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Created over 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

Build Status Size Zenodo PyPSA-Eur Snakemake <!--Zenodo PyPSA-Eur-Sec--> <!--REUSE status--> <!--Stack Exchange questions.-->

PyPSA-FES: A linear optimisation model to simulate Great Britain's energy transition

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.

PyPSA-Eur Grid Model

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.

Energy Flows Modelled in PyPSA-FES

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.

Contributing and Support

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 lukas.franken@ed.ac.uk. - For bugs and feature requests, please use the PyPSA-FES Github Issues page.

Licence

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.

Owner

  • Name: Lukas Franken
  • Login: LukasFrankenQ
  • Kind: user
  • Location: Edinburgh, UK

PhD student in Energy System Modelling and Machine Learning at the University of Edinburgh. Also working with Octopus Energy on modelling electricity markets.

GitHub Events

Total
Last Year

Committers

Last synced: almost 2 years ago

All Time
  • Total Commits: 2,290
  • Total Committers: 54
  • Avg Commits per committer: 42.407
  • Development Distribution Score (DDS): 0.696
Past Year
  • Commits: 237
  • Committers: 3
  • Avg Commits per committer: 79.0
  • Development Distribution Score (DDS): 0.346
Top Committers
Name Email Commits
Fabian Neumann f****n@o****e 696
Jonas Hörsch j****h@k****u 232
Fabian f****f@g****e 193
Tom Brown t****m@n****g 180
LukasFrankenQ l****n@g****m 163
lisazeyen l****n@w****e 138
martavp m****z@g****m 116
pre-commit-ci[bot] 6****] 87
LukasFrankenQ l****n@e****k 79
martacki m****i@k****u 78
Adam-Dvorak1 9****1 63
virio-andreyana 1****a 27
Max Parzen m****n@e****k 26
Parisra 1****a 25
euronion 4****n 22
Philipp Glaum p****m@t****e 17
Jeroen Peters h****s@g****m 15
Markus Millinger 5****s 12
Gorm Bruun Andresen g****a@e****k 11
Koen van Greevenbroek k****k@u****o 10
Leon 5****n 8
energyls l****m@o****e 8
Fabian Hofmann h****n@u****e 7
Irieo i****n@g****m 7
Ebbe Kyhl 6****l 7
Jan Frederick j****r@i****e 6
Martha Maria 5****4 6
Julio Pascual 1****l 5
eb5194 e****4@i****u 4
Seth s****n@g****m 4
and 24 more...

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 1
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • drzekunguo (1)
Pull Request Authors
Top Labels
Issue Labels
bug (1)
Pull Request Labels

Dependencies

.github/workflows/ci.yaml actions
  • actions/cache v3 composite
  • actions/checkout v3 composite
  • actions/upload-artifact v3 composite
  • conda-incubator/setup-miniconda v2 composite
.github/workflows/container.yaml actions
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  • google-github-actions/setup-gcloud v0.2.0 composite
.github/workflows/lint_and_test.yaml actions
  • actions/cache v3 composite
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
Dockerfile docker
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  • python 3.9.6-slim-buster build
Pipfile pypi
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