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Improved selection of critical network elements for flow-based market coupling based on congestion patterns

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  • Schönheit, David
  • Bruninx, Kenneth
  • Kenis, Michiel
  • Möst, Dominik

Abstract

European electricity markets are zonal markets, a set-up that naturally entails an imperfect representation of intra-zonal congestion patterns that may limit cross-border trade. The method of flow-based market coupling aims to reflect limitations to cross-border trade by incorporating intra- and interzonal grid elements within the setting of zonal pricing through monitoring the flows on these critical network elements caused by inter-zonal trade. A major challenge for grid operators is the selection of critical network elements, essentially deciding which grid elements send congestion signals and trade limitations to the markets. Our main research question is: Can insights on hypothetically re-configured market zones help to improve the selection of critical network elements and lead to cost reductions without effectively changing the market zone setting? Using a flow-based market coupling optimization model based on a 3-zone test network, we propose a hypothetical nodal price-based market zone re-configuration to identify congestion signals and derive an improved set of critical network elements. We find that around 90% of the cost reductions from this market zone re-configuration can be maintained when the critical network elements, obtained from the re-configured market zones, are used in the original 3-zone setting. This is a strong indication that, both in reality as well as model-based research of flow-based market coupling, the selection of critical network elements should be based on expected congestion patterns. The proposed approach can constitute a helpful addition to static and assumption-based selection criteria for critical network elements that are currently used by European grid operators.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:306:y:2022:i:pa:s0306261921013258
    DOI: 10.1016/j.apenergy.2021.118028
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    References listed on IDEAS

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    Cited by:

    1. Bakhshideh Zad, Bashir & Toubeau, Jean-François & Bruninx, Kenneth & Vatandoust, Behzad & De Grève, Zacharie & Vallée, François, 2022. "Supervised learning-assisted modeling of flow-based domains in European resource adequacy assessments," Applied Energy, Elsevier, vol. 325(C).
    2. Ovaere, Marten & Kenis, Michiel & Van den Bergh, Kenneth & Bruninx, Kenneth & Delarue, Erik, 2023. "The effect of flow-based market coupling on cross-border exchange volumes and price convergence in Central Western European electricity markets," Energy Economics, Elsevier, vol. 118(C).
    3. Kenis, Michiel & Bruninx, Kenneth & Delarue, Erik, 2024. "Regulatory incentives for transmission system operators under flow-based market coupling," Utilities Policy, Elsevier, vol. 87(C).
    4. Borbáth, Tamás & Van Hertem, Dirk, 2024. "Appropriate transmission grid representation for European resource adequacy assessments," Applied Energy, Elsevier, vol. 355(C).

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    More about this item

    Keywords

    Critical network elements; Flow-based market coupling; Market zones; Nodal and zonal markets; Zone re-configuration;
    All these keywords.

    JEL classification:

    • 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
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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