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The Benefit of Coordinating Congestion Management in Germany


  • Friedrich Kunz
  • Alexander Zerrahn


The management of congestion within the German electricity transmission network has become more important during the last years. This emerging relevance is caused by the increase of renewable generation and the partial phaseout of nuclear power plants. Both developments yield a change in the transmission flow pattern and thus the need for congestion management. Currently, four German transmission system operators (TSOs) are in charge of managing congestion using curative methods, particularly re-dispatch of power plants. However, the existence of four TSOs within Germany induces the question whether coordination between them in managing national congestion would be beneficial. To address this issue, we apply a generalized Nash equilibrium model to analyze different degrees of coordination, covering the German electricity market with a detailed representation of the generation and network structure. Our results indicate that the costs of congestion management decrease in a rising degree of coordination as TSOs take into account congestion in other operators' zones. Total costs are highest in case each TSO is solely responsible for its own zone, and lowest if one integrated entity is in charge of mitigating congestion. We conclude that, in a setup with multiple TSOs, inducing coordination, for instance through a common market, has the potential of lowering the overall costs of congestion management.

Suggested Citation

  • Friedrich Kunz & Alexander Zerrahn, 2013. "The Benefit of Coordinating Congestion Management in Germany," Discussion Papers of DIW Berlin 1298, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1298

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    References listed on IDEAS

    1. Neuhoff, Karsten & Barquin, Julian & Bialek, Janusz W. & Boyd, Rodney & Dent, Chris J. & Echavarren, Francisco & Grau, Thilo & von Hirschhausen, Christian & Hobbs, Benjamin F. & Kunz, Friedrich & Nabe, 2013. "Renewable electric energy integration: Quantifying the value of design of markets for international transmission capacity," Energy Economics, Elsevier, vol. 40(C), pages 760-772.
    2. Friedrich Kunz, 2013. "Improving Congestion Management: How to Facilitate the Integration of Renewable Generation in Germany," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    3. Florian Leuthold & Hannes Weigt & Christian Hirschhausen, 2012. "A Large-Scale Spatial Optimization Model of the European Electricity Market," Networks and Spatial Economics, Springer, vol. 12(1), pages 75-107, March.
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    Cited by:

    1. Oseni, Musiliu O. & Pollitt, Michael G., 2016. "The promotion of regional integration of electricity markets: Lessons for developing countries," Energy Policy, Elsevier, vol. 88(C), pages 628-638.
    2. Zerrahn, Alexander & Huppmann, Daniel, 2014. "Network Expansion to Mitigate Market Power: How Increased Integration Fosters Welfare," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100459, Verein für Socialpolitik / German Economic Association.
    3. Oseni, Musiliu O. & Pollitt, Michael G., 2014. "Institutional arrangements for the promotion of regional integration of electricity markets : international experience," Policy Research Working Paper Series 6947, The World Bank.
    4. Katrin Trepper & Michael Bucksteeg & Christoph Weber, 2013. "An integrated approach to model redispatch and to assess potential benefits from market splitting in Germany," EWL Working Papers 1319, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Apr 2014.
    5. repec:eee:rensus:v:82:y:2018:i:p3:p:3452-3467 is not listed on IDEAS
    6. Trepper, Katrin & Bucksteeg, Michael & Weber, Christoph, 2015. "Market splitting in Germany – New evidence from a three-stage numerical model of Europe," Energy Policy, Elsevier, vol. 87(C), pages 199-215.
    7. Thao Pham, 2015. "Energiewende and competition in Germany: Diagnosing market power in wholesale electricity market," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2015(2), pages 29-49.

    More about this item


    Congestion Management; Coordination; Electricity Economics; Generalized Nash Equilibrium; Germany;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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