PyPSA-PL is an implementation of the energy modelling framework PyPSA shipped with a use-ready dataset tailored for the Polish energy system. PyPSA-PL can be used to plan optimal investments in the power, heating, hydrogen, and light vehicle sectors – given final-use demand together with capital and operational costs for assets – or to optimise the hourly dispatch of utility units – given final-use demand and operational costs only. Starting with v3.1 (released in 2025), the model can operate on 16 voivodeship-level nodes and accounts for transmission and distribution expansion costs. All that makes it a valuable tool for investigating the feasibility of decarbonisation scenarios for the Polish energy system, in which a large share of electricity is supplied by variable sources such as wind and solar.
PyPSA-PL has been developed and tested using Python 3.10. The project dependencies can be installed using the Poetry tool according to the pyproject.toml file. Alternatively, you can use any other Python package manager – the dependencies are also listed in the requirements.txt file. Additionally, you will need to install an external solver (see PyPSA manual).
PyPSA-PL-mini notebooks can be deployed on the Google Colab platform. To do so, navigate to one of the PyPSA-PL-mini application notebooks in the notebooks directory. In the notebook, click the "Open in Colab" banner and follow the instructions provided therein.
This table lists the main input data sources and data generation tools. More detailed source attribution can be found in the input spreadsheets themselves.
| Input | Source |
|---|---|
| Technology and carrier definitions | Kubiczek P. (2025). Technology and carrier definitions for PyPSA-PL model. Instrat. |
| Technological and cost assumptions | Kubiczek P., Żelisko W. (2025). Technological and cost assumptions for PyPSA-PL model. Instrat. |
| Installed capacity assumptions | Kubiczek P. (2025). Installed capacity assumptions for PyPSA-PL model. Instrat. |
| Annual energy flow assumptions | Kubiczek P. (2025). Annual energy flow assumptions for PyPSA-PL model. Instrat. |
| Capacity utilisation assumptions | Kubiczek P. (2025). Capacity utilisation assumptions for PyPSA-PL model. Instrat. |
| Installed capacity potential and maximum addition assumptions | Kubiczek P. (2025). Installed capacity potential and maximum addition assumptions for PyPSA-PL model. Instrat. |
| Electricity final use time series | ENTSO-E. (2023). Total Load—Day Ahead / Actual. Transparency Platform. https://transparency.entsoe.eu/load-domain/r2/totalLoadR2/show |
| Wind and solar PV availability time series | Hofmann, F., Hampp, J., Neumann, F., Brown, T., Hörsch, J. (2021). atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series. Journal of Open Source Software, 6, 3294. https://doi.org/10.21105/joss.03294 |
| Temperature data used to infer space heating demand and heat pump COP time series | IMGW. (2023). Dane publiczne. Instytut Meteorologii i Gospodarki Wodnej. https://danepubliczne.imgw.pl/ |
| Daily space heating demand time series | Ruhnau, O., Muessel, J. (2023). When2Heat Heating Profiles. Open Power System Data. https://doi.org/10.25832/when2heat/2023-07-27 |
| Traffic data used to infer light vehicle mobility and BEV charging time series | GDDKiA. (2023). Stacje Ciągłych Pomiarów Ruchu (SCPR). Generalna Dyrekcja Dróg Krajowych i Autostrad. https://www.gov.pl/web/gddkia/stacje-ciaglych-pomiarow-ruchu |
| Power transmission grid | JAO. (2024). Static Grid Model (6th release). Joint Allocation Office. https://www.jao.eu/static-grid-model |
Here you can find the list of publications based on the PyPSA-PL results and links to the full datasets stored in Zenodo.
- Kubiczek P., Nowak K., Smoleń M. (2025). Sieci na miarę. Koszty sieciowe a opłacalność OZE w Polsce do 2040 r. Instrat Policy Paper 03/2025. (awaiting translation into English)
https://instrat.pl/sieci-a-oze
- Kubiczek P., Smoleń M. (2024). Three challenging decades. Scenario for the Polish energy transition out to 2050. Instrat Policy Paper 03/2024. https://instrat.pl/three-challenging-decades/
- Kubiczek P., Smoleń M., Żelisko W. (2023). Poland approaching carbon neutrality. Four scenarios for the Polish energy transition until 2040. Instrat Policy Paper 06/2023. https://instrat.pl/poland-2040/
- Kubiczek P. (2023). Baseload power. Modelling the costs of low flexibility of the Polish power system. Instrat Policy Paper 04/2023. https://instrat.pl/baseload-power/
- Kubiczek P., Smoleń M. (2023). Poland cannot afford medium ambitions. Savings driven by fast deployment of renewables by 2030. Instrat Policy Paper 03/2023. https://instrat.pl/pypsa-march-2023/
The current version of PyPSA-PL is a successor of the PyPSA-PL v1 developed by Instrat in 2021. The following publications were based on the PyPSA-PL v1 results:
- Czyżak, P., Wrona, A. (2021). Achieving the goal. Coal phase-out in Polish power sector. Instrat Policy Paper 01/2021. https://instrat.pl/coal-phase-out
- Czyżak, P., Sikorski, M., Wrona, A. (2021). What’s next after coal? RES potential in Poland. Instrat Policy Paper 06/2021. https://instrat.pl/res-potential
- Czyżak, P., Wrona, A., Borkowski, M. (2021). The missing element. Energy security considerations. Instrat Policy Paper 09/2021. https://instrat.pl/energy-security
The code is released under the MIT license. The input and output data are released under the CC BY 4.0 license.
© Fundacja Instrat 2025
