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Open Power System Data – Frictionless data for electricity system modelling

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  • Wiese, Frauke
  • Schlecht, Ingmar
  • Bunke, Wolf-Dieter
  • Gerbaulet, Clemens
  • Hirth, Lion
  • Jahn, Martin
  • Kunz, Friedrich
  • Lorenz, Casimir
  • Mühlenpfordt, Jonathan
  • Reimann, Juliane
  • Schill, Wolf-Peter

Abstract

The quality of electricity system modelling heavily depends on the input data used. Although a lot of data is publicly available, it is often dispersed, tedious to process and partly contains errors. We argue that a central provision of input data for modelling has the character of a public good: it reduces overall societal costs for quantitative energy research as redundant work is avoided, and it improves transparency and reproducibility in electricity system modelling. This paper describes the Open Power System Data platform that aims at realising the efficiency and quality gains of centralised data provision by collecting, checking, processing, aggregating, documenting and publishing data required by most modellers. We conclude that the platform can provide substantial benefits to energy system analysis by raising efficiency of data pre-processing, providing a method for making data pre-processing for energy system modelling traceable, flexible and reproducible and improving the quality of original data published by data providers.

Suggested Citation

  • Wiese, Frauke & Schlecht, Ingmar & Bunke, Wolf-Dieter & Gerbaulet, Clemens & Hirth, Lion & Jahn, Martin & Kunz, Friedrich & Lorenz, Casimir & Mühlenpfordt, Jonathan & Reimann, Juliane & Schill, Wolf-P, 2019. "Open Power System Data – Frictionless data for electricity system modelling," Applied Energy, Elsevier, vol. 236(C), pages 401-409.
    • Handle: RePEc:eee:appene:v:236:y:2019:i:c:p:401-409
    DOI: 10.1016/j.apenergy.2018.11.097
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    2. Günther, Claudia & Schill, Wolf-Peter & Zerrahn, Alexander, 2021. "Prosumage of solar electricity: Tariff design, capacity investments, and power sector effects," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 152.
    3. Schill, Wolf-Peter & Zerrahn, Alexander, 2020. "Flexible electricity use for heating in markets with renewable energy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 266.
    4. Gambardella, Christian & Pahle, Michael & Schill, Wolf-Peter, 2020. "Do Benefits from Dynamic Tariffing Rise? Welfare Effects of Real-Time Retail Pricing Under Carbon Taxation and Variable Renewable Electricity Supply," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 75(1), pages 183-213.
    5. Yongrui Qin & Meng Zhao & Qingcheng Lin & Xuefeng Li & Jing Ji, 2022. "Data-Driven Building Energy Consumption Prediction Model Based on VMD-SA-DBN," Mathematics, MDPI, vol. 10(17), pages 1-10, August.
    6. Héctor Marañón-Ledesma & Asgeir Tomasgard, 2019. "Analyzing Demand Response in a Dynamic Capacity Expansion Model for the European Power Market," Energies, MDPI, vol. 12(15), pages 1-24, August.
    7. Valentin Mahler & Robin Girard & Georges Kariniotakis, 2021. "Data-driven Structural Modeling of Electricity Price Dynamics," Working Papers hal-03445396, HAL.
    8. Mahler, Valentin & Girard, Robin & Kariniotakis, Georges, 2022. "Data-driven structural modeling of electricity price dynamics," Energy Economics, Elsevier, vol. 107(C).
    9. Md. Nasimul Islam Maruf, 2021. "A Novel Method for Analyzing Highly Renewable and Sector-Coupled Subnational Energy Systems—Case Study of Schleswig-Holstein," Sustainability, MDPI, vol. 13(7), pages 1-24, March.
    10. Zech, Matthias & von Bremen, Lueder, 2024. "End-to-end learning of representative PV capacity factors from aggregated PV feed-ins," Applied Energy, Elsevier, vol. 361(C).
    11. Claudia Gunther & Wolf-Peter Schill & Alexander Zerrahn, 2019. "Prosumage of solar electricity: tariff design, capacity investments, and power system effects," Papers 1907.09855, arXiv.org.
    12. Daniel Wuebben & Juan Romero-Luis & Manuel Gertrudix, 2020. "Citizen Science and Citizen Energy Communities: A Systematic Review and Potential Alliances for SDGs," Sustainability, MDPI, vol. 12(23), pages 1-24, December.
    13. Arjuna Nebel & Julián Cantor & Sherif Salim & Amro Salih & Dixit Patel, 2022. "The Role of Renewable Energies, Storage and Sector-Coupling Technologies in the German Energy Sector under Different CO 2 Emission Restrictions," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    14. Fabian Stöckl & Alexander Zerrahn, 2023. "Substituting Clean for Dirty Energy: A Bottom-Up Analysis," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 10(3), pages 819-863.
    15. Viktorija Bobinaite & Marialaura Di Somma & Giorgio Graditi & Irina Oleinikova, 2019. "The Regulatory Framework for Market Transparency in Future Power Systems under the Web-of-Cells Concept," Energies, MDPI, vol. 12(5), pages 1-26, March.
    16. Jens Weibezahn & Mario Kendziorski, 2019. "Illustrating the Benefits of Openness: A Large-Scale Spatial Economic Dispatch Model Using the Julia Language," Energies, MDPI, vol. 12(6), pages 1-21, March.
    17. Drücke, Jaqueline & Borsche, Michael & James, Paul & Kaspar, Frank & Pfeifroth, Uwe & Ahrens, Bodo & Trentmann, Jörg, 2021. "Climatological analysis of solar and wind energy in Germany using the Grosswetterlagen classification," Renewable Energy, Elsevier, vol. 164(C), pages 1254-1266.
    18. Javier L'opez Prol & Wolf-Peter Schill, 2020. "The Economics of Variable Renewables and Electricity Storage," Papers 2012.15371, arXiv.org.
    19. Alexander Roth & Carlos Gaete-Morales & Dana Kirchem & Wolf-Peter Schill, 2023. "Power sector benefits of flexible heat pumps," Papers 2307.12918, arXiv.org, revised Oct 2024.
    20. Lledó, Llorenç & Ramon, Jaume & Soret, Albert & Doblas-Reyes, Francisco-Javier, 2022. "Seasonal prediction of renewable energy generation in Europe based on four teleconnection indices," Renewable Energy, Elsevier, vol. 186(C), pages 420-430.

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