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Systems","sub_category":"Global and Regional Energy System Models","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# PyPSA-DE - Hochaufgelöstes, sektorengekoppeltes Modell des deutschen Energiesystems\n\nPyPSA-DE ist ein sektorengekoppeltes Energiesystem-Modell auf Basis der Toolbox [PyPSA](https://github.com/PyPSA/pypsa) und des europäischen Modells [PyPSA-Eur](https://github.com/PyPSA/pypsa-eur). Der PyPSA-DE Workflow modelliert das deutsche Energiesystem mit deutschlandspezifischen Datensätzen (MaStR, Netzentwicklungsplan,...) im Verbund mit den direkten Stromnachbarn sowie Spanien und Italien. Der Ausbau und der Betrieb von Kraftwerken, des  Strom- und Wasserstoffübertragunsnetzes und die Energieversorgung aller Sektoren werden dann in einem linearen Optimierungsproblem gelöst, mit hoher zeitlicher und räumlicher Auflösung. PyPSA-DE wurde im Rahmen des Kopernikus-Projekts [Ariadne](https://ariadneprojekt.de/) entwickelt in dem Szenarien für ein klimaneutrales Deutschland untersucht werden, und spielt eine zentrale Rolle im [Ariadne Szenarienreport](https://ariadneprojekt.de/publikation/report-szenarien-zur-klimaneutralitat-2045/), als Leitmodell für den [Sektor Energiewirtschaft und Infrastruktur](https://ariadneprojekt.de/publikation/report-szenarien-zur-klimaneutralitat-2045/#6-sektorale-perspektive-energiewirtschaft) und als eines von drei Gesamtsystemmodellen. Die Ergebnisse aus der Modellierung mit PyPSA-DE werden auch im [Ariadne-Webinar zu den Kernaussagen des Berichts](https://youtu.be/UL3KAH7e0zs) ([Folien](https://ariadneprojekt.de/media/2025/03/Ariadne_Szen2025_Webinar_Folien_Kernaussagen.pdf)) und im [Ariadne-Webinar zur Energiewirtschaft](https://youtu.be/FcmHBL1MKQA) ([Folien](https://ariadneprojekt.de/media/2025/03/Ariadne_Szen2025_Webinar_Folien_Energiewirtschaft.pdf)) vorgestellt. Die [gelösten Netzwerke](https://zenodo.org/records/15096970) sind auf zenodo verfügbar.\n\n# PyPSA-DE - High resolution, sector-coupled model of the German Energy System\n\nPyPSA-DE is a sector-coupled energy system model based on the toolbox [PyPSA](https://github.com/PyPSA/pypsa) and the European model [PyPSA-Eur](https://github.com/PyPSA/pypsa-eur). It solves a linear optimization problem to simulate the electricty and hydrogen transmission networks, as well as supply, demand and storage in all sectors of the energy system in Germany and its neighboring countries, as well as Italy and Spain, with high spatial and temporal resolution. PyPSA-DE was developed in the context of the Kopernikus-Projekt [Ariadne](https://ariadneprojekt.de/en/), which studies scenarios of a carbon-neutral German economcy, and plays a decisive role in the [Ariadne Szenarienreport](https://ariadneprojekt.de/publikation/report-szenarien-zur-klimaneutralitat-2045/), as reference model for the [energy and infrastructure sectors](https://ariadneprojekt.de/publikation/report-szenarien-zur-klimaneutralitat-2045/#6-sektorale-perspektive-energiewirtschaft). The results of modeling with PyPSA-DE are also presented in the [Ariadne-Webinar on the core messages of the report](https://youtu.be/UL3KAH7e0zs) ([slides](https://ariadneprojekt.de/media/2025/03/Ariadne_Szen2025_Webinar_Folien_Kernaussagen.pdf)) and in the [Ariadne-Webinar on the energy sector](https://youtu.be/FcmHBL1MKQA) ([slides](https://ariadneprojekt.de/media/2025/03/Ariadne_Szen2025_Webinar_Folien_Energiewirtschaft.pdf)). The [solved networks](https://zenodo.org/records/15096970) are available on zenodo.\n\nThis repository contains the entire scientific project, including data sources and code. The philosophy behind this repository is that no intermediary results are included, but all results are computed from raw data and code.\n\n[\u003cimg src=\"https://ariadneprojekt.de/media/2025/03/Abb-7.3.png\" width=\"400\"/\u003e](https://ariadneprojekt.de/media/2025/03/Abb-7.3.png)\n\n## Getting ready\n\nFirst of all, clone the PyPSA-DE repository using the version control system git in the command line.\n```\ngit clone https://github.com/PyPSA/pypsa-de.git\n```\n\nPyPSA-DE relies on a set of other Python packages to function. We manage these using [`pixi`](https://pixi.prefix.dev/latest/). Once pixi is installed, you can activate the project environment for your operating system and have access to all the PyPSA-DE dependencies from the command line:\n```\npixi shell\n```\n\nTip: You can also set up automatic shell activation in several popular editors (e.g. in VSCode or Zed). Refer to the pixi documentation for the most up-to-date options.\n\nIf you cannot access pixi on your machine, you can also install using `conda`. For more details see the corresponding section in the [documentation](https://pypsa-eur.readthedocs.io/en/latest/installation.html#legacy-method-conda) of PyPSA-Eur\n\n## Run the analysis\n\nBefore running any analysis with scenarios, the rule `build_scenarios` must be executed. This will create the file `config/scenarios.automated.yaml` which includes input data and CO2 targets from the IIASA Ariadne database as well as the specifications from the manual scenario file. [This file is specified in the  config.de.yaml via they key `run:scenarios:manual_file` and located at `config/scenarios.manual.yaml` by default].\n\n    snakemake -c1 build_scenarios\n\nNote that the hierarchy of scenario files is the following: `scenarios.automated.yaml` \u003e (any `explicitly specified --configfiles`) \u003e `config.de.yaml `\u003e `config.default.yaml `Changes in the file `scenarios.manual.yaml `are only taken into account if the rule `build_scenarios` is executed.\n\nTo run the analysis use, either\n\n    snakemake -call  # The flag -cN specifies the number N of CPU cores available to snakemake\n\nto generate the solved networks, or\n\n    snakemake -c1 ariadne_all \n\nwhich will generators additional outputs related to the Ariadne project. If you would like to use more computational resources you may increase the number of cores by adding, e.g. `-c4` to the call to get only 4 cores, or `-call` to use all cores. For more option please refer to the [snakemake](https://snakemake.readthedocs.io/en/stable/) documentation.\n\n## Repo structure\n\n* `config`: configuration files, most importantly `config.de.yaml` and `scenarios.manual.yaml`\n* `data/pypsa-de`: Germany specific data\n* `scripts`: contains the Python scripts for the workflow, the pypsa-de specific code needed to run this repo is contained in `scripts/pypsa-de`\n* `cutouts`: very large weather data cutouts supplied by atlite library (does not exist initially)\n* `data`: place for raw data (does not exist initially)\n* `resources`: place for intermediate/processing data for the workflow (does not exist initially)\n* `results`: will contain all results (does not exist initially)\n* `logs` and `benchmarks`\n* The `Snakefile` contains the PyPSA-DE specific snakemake workflow\n\n## Differences to PyPSA-EUR\n\nPyPSA-DE is a softfork of PyPSA-EUR. As such, large parts of the functionality are similar, and the [documentation](https://pypsa-eur.readthedocs.io/en/latest/) of PyPSA-Eur is a good starting point to get acquainted with the model. On top of that, PyPSA-DE adds several data sources and workflow steps that improve the representation of the German Energy System. Below is a non-conclusive list of the most important changes.\n\n- Default resolution of 16 regions in Germany and 13 region for neighboring countries\n- 10 pre-defined scenarios (1 Current Policies, 3 Net-Zero Scenarios (Balanced, Focus H2, Focus Electricity), 2 Demand Variations based on the Balanced Scenario, 4 Demand Variations Based on the Current Policies Scenario)\n- Specific cost assumption for Germany:\n  - Gas, Oil, Coal prices\n  - electrolysis and heat-pump costs\n  - Infrastructure costs [according to the Netzentwicklungsplan](https://github.com/PyPSA/pypsa-ariadne/pull/193) 2021 and 2023\n  - option for pessimstic, mean and optimistic cost development\n- Transport and Industry demands as well as heating stock imported from the sectoral models in the Ariadne consortium ([Aladin](https://ariadneprojekt.de/modell-dokumentation-aladin/), [REMOD](https://ariadneprojekt.de/modell-dokumentation-remod/), [FORECAST](https://ariadneprojekt.de/modell-dokumentation-forecast/) and [REMIND](https://ariadneprojekt.de/modell-dokumentation-remind/))\n- More detailed data on CHPs in Germany\n- The model has been validated against 2020 electricity data for Germany\n- National CO2-Targets according to the Klimaschutzgesetz\n- Additional constraints that limit maximum capacity of specific technologies\n- Import constraints on Efuels, hydrogen and electricity\n- Renewable build out according to the Wind-an-Land, Wind-auf-See and Solarstrategie laws\n- A comprehensive reporting  module that exports Capacity Expansion, Primary/Secondary/Final Energy, CO2 Emissions per Sector, Trade, Investments, and more.\n- Plotting functionality to compare different scenarios\n- Electricity Network development until 2030 (and for AC beyond) according to the NEP23\n- Offshore development until 2030 according to the Offshore NEP23\n- Hydrogen network development until 2028 according to the Wasserstoffkernnetz. PCI / IPCEI projects for later years are included as well.\n- `costs:horizon` - specify if technology costs are expected to follow an `optimistic, mean` or `pessimistic` trajectory\n\n## New Config Options\n\n- `pypsa-de` - interaction with IIASA database. Specify a database, and `leitmodelle` for demand and co2 emissions data in specific sectors\n- `wasserstoff_kernnetz` - configure which parts of the Wasserstoff Kernnetz should be included in the model\n- `new_decentral_fossil_boiler_ban` - specify in which country and which years to ban fossil boilers\n- `coal_generation_ban` - specify in which country and which years to ban electricity generation from coal\n- `nuclear_generation_ban` - specify in which country and which years to ban electricity generation from nuclear\n- `first_technology_occurrence` - specify the year form which on specific technologies are available\n- `solving:constraints` - specify PyPSA-DE specific limits, e.g. on capacity, trade and generation\n- `co2_budget_DE_source` specify the carbon trajectory for Germany: Following the projections of the Umweltbundestamt (`UBA`) or targeting net zero with the Klimaschutzgesetz(`KSG`)\n- `costs:transmission` - specify  if new HVDC links should be built with `overhead` or `underground` cables. the basic cost assumptions of the Netzentwicklungsplan (`2021,2023`) can be changed by using one of the two corresponding `custom_cost_nep_*.csv` files provided in the `data/pypsa-de` folder\n\n## Data sources\n\n`data/pypsa-de/data/pypsa-debase.csv`\n\n* **Source:** Kopernikus Projekt Ariadne\n* **Link:** [Szenarien-Explorer](https://ariadne2.apps.ece.iiasa.ac.at/explorer)\n* **License:** CC-BY 4.0\n* **Description:** Results from the [Ariadne Report: Die Energiewende kosteneffizient gestalten](https://ariadneprojekt.de/publikation/report-szenarien-zur-klimaneutralitat-2045/)\n\n## License\n\nThe code in this repo is MIT licensed, see `./LICENSE.md`.\n\n\u003e [!NOTE]\n\u003e Find below the original `README.md` from [PyPSA-Eur](https://github.com/PyPSA/PyPSA-Eur)\n\n\u003c!--\nSPDX-FileCopyrightText: Contributors to PyPSA-Eur \u003chttps://github.com/pypsa/pypsa-eur\u003e\nSPDX-License-Identifier: CC-BY-4.0\n--\u003e\n\n![GitHub release (latest by date including pre-releases)](https://img.shields.io/github/v/release/pypsa/pypsa-eur?include_prereleases)\n[![Test workflows](https://github.com/pypsa/pypsa-eur/actions/workflows/test.yaml/badge.svg)](https://github.com/pypsa/pypsa-eur/actions/workflows/test.yaml)\n[![Documentation](https://readthedocs.org/projects/pypsa-eur/badge/?version=latest)](https://pypsa-eur.readthedocs.io/en/latest/?badge=latest)\n![Size](https://img.shields.io/github/repo-size/pypsa/pypsa-eur)\n[![Zenodo PyPSA-Eur](https://zenodo.org/badge/DOI/10.5281/zenodo.3520874.svg)](https://doi.org/10.5281/zenodo.3520874)\n[![Zenodo PyPSA-Eur-Sec](https://zenodo.org/badge/DOI/10.5281/zenodo.3938042.svg)](https://doi.org/10.5281/zenodo.3938042)\n[![Snakemake](https://img.shields.io/badge/snakemake-≥9-brightgreen.svg?style=flat)](https://snakemake.readthedocs.io)\n[![Discord](https://img.shields.io/discord/911692131440148490?logo=discord)](https://discord.gg/AnuJBk23FU)\n[![REUSE status](https://api.reuse.software/badge/github.com/pypsa/pypsa-eur)](https://api.reuse.software/info/github.com/pypsa/pypsa-eur)\n\n# PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy System\n\nPyPSA-Eur is an open model dataset of the European energy system at the\ntransmission network level that covers the full ENTSO-E area and all energy sectors, including transport, heating, biomass, industry, and agriculture.\nBesides the power grid, pipeline networks for gas, hydrogen, carbon dioxide, and liquid fuels are included.\nThe model is suitable both for planning studies and operational studies.\nThe model is built from open data using a Snakemake workflow and fully open source.\nIt is designed to be imported into the open-source energy system modelling framework [PyPSA](www.pypsa.org).\n\nThe model is described in the [documentation](https://pypsa-eur.readthedocs.io)\nand in the paper\n[PyPSA-Eur: An Open Optimisation Model of the European Transmission\nSystem](https://arxiv.org/abs/1806.01613), 2018,\n[arXiv:1806.01613](https://arxiv.org/abs/1806.01613).\nThe model building routines are defined through a snakemake workflow.\nPlease see the [documentation](https://pypsa-eur.readthedocs.io/)\nfor installation instructions and other useful information about the snakemake workflow.\nThe model is designed to be imported into the open toolbox\n[PyPSA](https://github.com/PyPSA/PyPSA).\n\n\u003e [!NOTE]\n\u003e PyPSA-Eur has many contributors, with the maintenance currently led by the [Department of Digital Transformation in\n\u003e Energy Systems](https://tu.berlin/en/ensys) at the [Technical University of\n\u003e Berlin](https://www.tu.berlin).\n\u003e Previous versions were developed at the [Karlsruhe\n\u003e Institute of Technology](http://www.kit.edu/english/index.php) funded by the\n\u003e [Helmholtz Association](https://www.helmholtz.de/en/).\n\n\nAmong many other things, the dataset consists of:\n\n- A power grid model based on [OpenStreetMap](https://zenodo.org/records/18619025) for voltage levels above 220kV (optional above 60kV).\n- The open power plant database\n  [powerplantmatching](https://github.com/PyPSA/powerplantmatching).\n- Electrical demand time series from the [ENTSO-E Transparency Platform](https://transparency.entsoe.eu/).\n- Renewable time series based on ERA5 and SARAH-3, assembled using [atlite](https://github.com/PyPSA/atlite).\n- Geographical potentials for wind and solar generators based land eligibility analysis in [atlite](https://github.com/PyPSA/atlite).\n- Energy balances compiled from Eurostat and JRC-IDEES datasets.\n\nThe high-voltage grid and the power plant fleet are shown in this map of the unclustered model (as of 1 January 2026):\n\n![PyPSA-Eur Unclustered](doc/img/base.png)\n\n\nFor computational reasons the model is usually clustered down\nto 50-250 nodes. The image below shows the electricity network and power plants clustered to NUTS2 regions:\n\n![network diagram](doc/img/elec.png)\n\nThis diagram gives an overview of the sectors and the links between\nthem within each model region:\n\n![sector diagram](doc/img/multisector_figure.png)\n\n\n\n# Warnings\n\nPyPSA-Eur is under active development and has several\n[limitations](https://pypsa-eur.readthedocs.io/en/latest/limitations.html) which\nyou should understand before using the model. The github repository\n[issues](https://github.com/PyPSA/pypsa-eur/issues) collect known topics we are\nworking on (please feel free to help or make suggestions). The\n[documentation](https://pypsa-eur.readthedocs.io/) remains somewhat patchy. You\ncan find showcases of the model's capabilities in the Joule paper [The potential\nrole of a hydrogen network in\nEurope](https://doi.org/10.1016/j.joule.2023.06.016), another [paper in Joule\nwith a description of the industry\nsector](https://doi.org/10.1016/j.joule.2022.04.016), or in [a 2021 presentation\nat EMP-E](https://nworbmot.org/energy/brown-empe.pdf). We do not recommend to\nuse the full resolution network model for simulations. At high granularity the\nassignment of loads and generators to the nearest network node may not be a\ncorrect assumption, depending on the topology of the underlying distribution\ngrid, and local grid bottlenecks may cause unrealistic load-shedding or\ngenerator curtailment. We recommend to cluster the network to a couple of\nhundred nodes to remove these local inconsistencies. See the discussion in\nSection 3.4 \"Model validation\" of the paper.\n\n# Contributing and Support\n\nWe 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.\n\n- To **discuss** with other PyPSA users, organise projects, share news, and get in touch with the community you can use the [Discord server](https://discord.gg/AnuJBk23FU).\n- For **bugs and feature requests**, please use the [PyPSA-Eur Github Issues page](https://github.com/PyPSA/pypsa-eur/issues).\n\n# Licence\n\nThe code in PyPSA-Eur is released as free software under the\n[MIT License](https://opensource.org/licenses/MIT), see [`doc/licenses.rst`](doc/licenses.rst).\nHowever, different licenses and terms of use may apply to the various\ninput data, see [`doc/data_sources.rst`](doc/data_sources.rst).\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.5281/zenodo.3520874","https://doi.org/10.5281/zenodo.3938042","https://doi.org/10.1016/j.joule.2023.06.016","https://doi.org/10.1016/j.joule.2022.04.016"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["energy-system-model","energy-system","power-systems","energy-model","pypsa","capacity-expansion-planning","energy-data","europe","power-grid","capacity-expansion-model"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/327092","html_url":"https://ost.ecosyste.ms/projects/327092"}