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Two prices fix all? On the Robustness of a German Bidding Zone Split

Author

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  • Zinke, Jonas

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI))

Abstract

As redispatch costs and their associated distributional impacts continue to rise,the discussion on reconfiguring bidding zones in European power markets persists. However, determining an appropriate bidding zone configuration is a non-trivial task, as it must prove beneficial under varying weather conditions, load situations, and an uncertain future, essentially necessitating persistent benefits. This paper uses the German-Luxembourg market area as an example to investigate the impact of uncertain factors, such as short-term weather patterns and long-term system changes, on the potential reduction of redispatch costs resulting from a two-zone split. Employing hierarchical clustering on hourly time series of Locational Marginal Prices for multiple historical weather and future scenario years, the paper derives bidding zone splits and assesses their robustness regarding redispatch cost reduction. Sensitivities to uncertain factors such as grid and renewable expansion, demand development, and fuel prices are investigated. The results indicate that a north-south split of the German-Luxembourg market area can robustly reduce redispatch costs.The impact on the reduction potential of yearly weather fluctuations is limited, owing to the structural nature of grid bottlenecks. However, the long-term transformations within the powersystem,coupled with their associated uncertainties, can significantly diminish the potential forcost reduction through a bidding zonesplit.

Suggested Citation

  • Zinke, Jonas, 2023. "Two prices fix all? On the Robustness of a German Bidding Zone Split," EWI Working Papers 2023-7, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI), revised 09 Jan 2024.
  • Handle: RePEc:ris:ewikln:2023_007
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    More about this item

    Keywords

    Market Design; Bidding Zone Review; Electricity Markets; Nodal Pricing; Energy System Modeling; Renewable Energies;
    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
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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