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Consistent and robust delimitation of price zones under uncertainty with an application to Central Western Europe

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  • Felling, Tim
  • Weber, Christoph

Abstract

New and alternative delimitations of price zones for Central Western Europe (CWE) might constitute a mid-term solution to cope with the increasing congestion in the electricity transmission grids. The significantly growing infeed from renewable energy sources puts more and more pressure on the grid and emphasizes the need for improved congestion management. Thus, a new delimitation of price zones is frequently considered in current discussions and research. The present paper applies a novel hierarchical cluster algorithm that clusters locational marginal prices and weights nodes depending on their demand- and supply situation to identify possible new price zone configurations (PZCs). The algorithm is applied in a scenario analysis of six scenarios reflecting main drivers that influence the future development of European Electricity markets in line with the trilemma of energy policy targets. Robustness of the new configuration is an important criterion for price zone configurations according to the European Guideline on Capacity Allocation and Congestion Management (CACM). Therefore, a robust price zone configuration is computed taking into account all the six individual scenarios. Results show that shape, size and price variations of price zones on the one hand strongly depend on the individual scenario. On the other hand, the identified robust configuration is shown to outperform other configurations, particularly also the current price zone configuration in CWE.

Suggested Citation

  • Felling, Tim & Weber, Christoph, 2018. "Consistent and robust delimitation of price zones under uncertainty with an application to Central Western Europe," Energy Economics, Elsevier, vol. 75(C), pages 583-601.
    • Handle: RePEc:eee:eneeco:v:75:y:2018:i:c:p:583-601
    DOI: 10.1016/j.eneco.2018.09.012
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Saez, Yago & Mochon, Asuncion & Corona, Luis & Isasi, Pedro, 2019. "Integration in the European electricity market: A machine learning-based convergence analysis for the Central Western Europe region," Energy Policy, Elsevier, vol. 132(C), pages 549-566.
    2. Ambrosius, M. & Egerer, J. & Grimm, V. & Weijde, A.H. van der, 2020. "Uncertain bidding zone configurations: The role of expectations for transmission and generation capacity expansion," European Journal of Operational Research, Elsevier, vol. 285(1), pages 343-359.
    3. Bucksteeg, Michael & Voswinkel, Simon & Blumberg, Gerald, 2023. "Improving flow-based market coupling by integrating redispatch potential - Evidence from a large-scale model," EconStor Preprints 270878, ZBW - Leibniz Information Centre for Economics.
    4. Schönheit, David & Bruninx, Kenneth & Kenis, Michiel & Möst, Dominik, 2022. "Improved selection of critical network elements for flow-based market coupling based on congestion patterns," Applied Energy, Elsevier, vol. 306(PA).
    5. Pöstges, Arne & Weber, Christoph, 2023. "Identifying key elements for adequate simplifications of investment choices – The case of wind energy expansion," Energy Economics, Elsevier, vol. 120(C).
    6. Marco Sebastian Breder & Felix Meurer & Michael Bucksteeg & Christoph Weber, 2022. "Spatial Incentives for Power-to-hydrogen through Market Splitting," EWL Working Papers 2203, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Jul 2022.
    7. Felling, Tim, 2021. "Development of a genetic algorithm and its application to a bi-level problem of system cost optimal electricity price zone configurations," Energy Economics, Elsevier, vol. 101(C).
    8. Schönheit, David & Bruninx, Kenneth & Kenis, Michiel & Möst, Dominik, 2021. "Improved selection of critical network elements for flow-based market coupling based on congestion patterns," EconStor Preprints 233467, ZBW - Leibniz Information Centre for Economics.
    9. Samuli Honkapuro & Jasmin Jaanto & Salla Annala, 2023. "A Systematic Review of European Electricity Market Design Options," Energies, MDPI, vol. 16(9), pages 1-26, April.
    10. Arne Pöstges & Christoph Weber, "undated". "Identifying key elements for adequate simplifications of investment choices - The case of wind energy expansion," EWL Working Papers 2101, University of Duisburg-Essen, Chair for Management Science and Energy Economics.

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    More about this item

    Keywords

    Cluster analysis; Electricity market design; Nodal pricing; Zonal pricing; Congestion management; Price zone configuration; Bidding zone configuration;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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