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Is smooth Energiewende possible? Improving the performance of climate policies in Germany by optimizing the risk of electricity delivery

Author

Listed:
  • Jakub Bandurski

    (University of Warsaw, Faculty of Economic Sciences)

  • Eliza Hałatek

    (University of Warsaw, Faculty of Economic Sciences)

  • Adam Łaziński

    (University of Warsaw, Faculty of Economic Sciences)

  • Michał Künstler

    (University of Warsaw, Faculty of Economic Sciences)

Abstract

The Energiewende is a deep-rooted notion in the German economy. The main goal is to achieve climate neutrality by transitioning to renewable energy sources. However, the feasibility of this transition is partially hindered by power grid congestion, which undermines system efficiency and leads to both economic and environmental costs. We address this issue by making a prediction of the likelihood of congestion occurrence within the German TenneT DE electricity network in the years 2020-2023. We propose a twofold approach offering a combination of advanced econometric models and state-of-the-art machine learning methods. We offer separate solutions for up congestion when additional energy needs to be pushed to the network as well as down congestion when energy needs to be pulled away from the network. Analyzing the CatBoost with XAI, we identify factors that play a significant role in driving redispatch events within the German electricity network.

Suggested Citation

  • Jakub Bandurski & Eliza Hałatek & Adam Łaziński & Michał Künstler, 2025. "Is smooth Energiewende possible? Improving the performance of climate policies in Germany by optimizing the risk of electricity delivery," Working Papers 2025-30, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2025-30
    as

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    File URL: https://www.wne.uw.edu.pl/download_file/6459/0
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    References listed on IDEAS

    as
    1. Feras Alasali & Khaled Nusair & Lina Alhmoud & Eyad Zarour, 2021. "Impact of the COVID-19 Pandemic on Electricity Demand and Load Forecasting," Sustainability, MDPI, vol. 13(3), pages 1-22, January.
    2. Marimoutou, Vêlayoudom & Soury, Manel, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Energy, Elsevier, vol. 88(C), pages 417-429.
    3. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Post-Print hal-01456125, HAL.
    4. Rodríguez, Rolando A. & Becker, Sarah & Andresen, Gorm B. & Heide, Dominik & Greiner, Martin, 2014. "Transmission needs across a fully renewable European power system," Renewable Energy, Elsevier, vol. 63(C), pages 467-476.
    5. Sievers, Luisa & Breitschopf, Barbara & Pfaff, Matthias & Schaffer, Axel, 2019. "Macroeconomic impact of the German energy transition and its distribution by sectors and regions," Ecological Economics, Elsevier, vol. 160(C), pages 191-204.
    6. Nardi, Y. & Rinaldo, A., 2011. "Autoregressive process modeling via the Lasso procedure," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 528-549, March.
    7. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," Working Papers halshs-01148746, HAL.
    8. Sharifzadeh, Mahdi & Lubiano-Walochik, Helena & Shah, Nilay, 2017. "Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 385-398.
    9. Renn, Ortwin & Marshall, Jonathan Paul, 2016. "Coal, nuclear and renewable energy policies in Germany: From the 1950s to the “Energiewende”," Energy Policy, Elsevier, vol. 99(C), pages 224-232.
    10. Glaum, Philipp & Hofmann, Fabian, 2023. "Leveraging the existing German transmission grid with dynamic line rating," Applied Energy, Elsevier, vol. 343(C).
    11. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    12. Davi-Arderius, Daniel & Schittekatte, Tim, 2023. "Carbon emissions impacts of operational network constraints: The case of Spain during the Covid-19 crisis," Energy Economics, Elsevier, vol. 128(C).
    13. Titz, Maurizio & Pütz, Sebastian & Witthaut, Dirk, 2024. "Identifying drivers and mitigators for congestion and redispatch in the German electric power system with explainable AI," Applied Energy, Elsevier, vol. 356(C).
    14. Andrew Curry, 2019. "Germany faces its future as a pioneer in sustainability and renewable energy," Nature, Nature, vol. 567(7749), pages 51-53, March.
    15. Davi-Arderius, Daniel & Schittekatte, Tim, 2023. "Environmental Impacts of Redispatching in Decarbonizing Electricity Systems: A Spanish Case Study," Working Papers 1-2023, Copenhagen Business School, Department of Economics.
    16. Byun, Sun-Joon & Park, Hyun-Sik & Yi, Sung-Jae & Song, Chul-Hwa & Choi, Young-Don & Lee, So-Hyeon & Shin, Jong-Keun, 2015. "Study on the optimal heat supply control algorithm for district heating distribution network in response to outdoor air temperature," Energy, Elsevier, vol. 86(C), pages 247-256.
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    Keywords

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    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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