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Coordinating Cross-Country Congestion Management

Author

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  • Friedrich Kunz
  • Alexander Zerrahn

Abstract

We employ a detailed two-stage model to simulate the operation of the Central Eastern European electricity market and network. Implementing different cases of coordination in congestion management between national transmission system operators, numerical results show the beneficial impact of closer cooperation. Specific steps comprise the sharing of network and dispatch information, cross-border counter-trading, and multilateral redispatch in a flow-based congestion management framework. Efficiency gains are accompanied by distributional effects. Closer economic cooperation becomes especially relevant against the background of changing spatial generation patterns, deeper international integration ofnational systems, and spillovers of national developments to adjacent systems.

Suggested Citation

  • Friedrich Kunz & Alexander Zerrahn, 2016. "Coordinating Cross-Country Congestion Management," Discussion Papers of DIW Berlin 1551, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1551
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    File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.527010.de/dp1551.pdf
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    References listed on IDEAS

    as
    1. Jan Abrell & Friedrich Kunz, 2015. "Integrating Intermittent Renewable Wind Generation - A Stochastic Multi-Market Electricity Model for the European Electricity Market," Networks and Spatial Economics, Springer, vol. 15(1), pages 117-147, March.
    2. Jonas Egerer & Clemens Gerbaulet & Richard Ihlenburg & Friedrich Kunz & Benjamin Reinhard & Christian von Hirschhausen & Alexander Weber & Jens Weibezahn, 2014. "Electricity Sector Data for Policy-Relevant Modeling: Data Documentation and Applications to the German and European Electricity Markets," Data Documentation 72, DIW Berlin, German Institute for Economic Research.
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    Cited by:

    1. Zepter, Jan Martin & Weibezahn, Jens, 2019. "Unit commitment under imperfect foresight – The impact of stochastic photovoltaic generation," Applied Energy, Elsevier, vol. 243(C), pages 336-349.
    2. Karel Janda & Jan Malek & Lukas Recka, 2017. "Influence of Renewable Energy Sources on Electricity Transmission Networks in Central Europe," Working Papers IES 2017/05, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2017.
    3. Karel Janda & Jan Malek & Lukas Recka, 2017. "The Influence of Renewable Energy Sources on the Czech Electricity Transmission System," Working Papers IES 2017/06, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2017.
    4. Bjørndal, Endre & Bjørndal, Mette & Cai, Hong & Panos, Evangelos, 2018. "Hybrid pricing in a coupled European power market with more wind power," European Journal of Operational Research, Elsevier, vol. 264(3), pages 919-931.
    5. Zerrahn, Alexander, 2017. "Wind Power and Externalities," Ecological Economics, Elsevier, vol. 141(C), pages 245-260.
    6. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.

    More about this item

    Keywords

    Electricity; congestion management; network modeling; Europe;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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