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Benefits of coordinating congestion management in electricity transmission networks: Theory and application to Germany

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  • Kunz, Friedrich
  • Zerrahn, Alexander
Abstract
This article analyzes the coordination of congestion management in the electricity grid and identifies the benefits from closer cooperation among Transmission System Operators. Mimicking the German situation with four Transmission System Operators in charge of relieving grid congestion, in particular by redispatch of power plants, we set up a model with shared transmission network constraints. Through different valuations of these constraints we consider cases of coordination. Based on a Generalized Nash Equilibrium model, we suggest an intuitive approach to introducing coordination. An application to German data provides evidence that more coordination is beneficial, providing channels through which redispatch volumes and specific costs are influenced. We discuss implications of our results for security of supply and network expansion.

Suggested Citation

  • Kunz, Friedrich & Zerrahn, Alexander, 2015. "Benefits of coordinating congestion management in electricity transmission networks: Theory and application to Germany," Utilities Policy, Elsevier, vol. 37(C), pages 34-45.
    • Handle: RePEc:eee:juipol:v:37:y:2015:i:c:p:34-45
    DOI: 10.1016/j.jup.2015.09.009
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    Cited by:

    1. 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.
    2. 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.
    3. Yang, Dong & Zhang, Lingge & Luo, Meifeng & Li, Feng, 2020. "Does shipping market affect international iron ore trade?– An equilibrium analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    4. Jonas Egerer, 2016. "Open Source Electricity Model for Germany (ELMOD-DE)," Data Documentation 83, DIW Berlin, German Institute for Economic Research.
    5. Jan Málek & Lukáš Recka & Karel Janda, 2017. "Impact of German Energiewende on transmission lines in the Central European region," CAMA Working Papers 2017-72, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Bucksteeg, Michael & Voswinkel, Simon & Blumberg, Gerald, 2024. "Improving flow-based market coupling by integrating redispatch potential―Evidence from a large-scale model," Energy Policy, Elsevier, vol. 188(C).
    7. Grimm, Veronika & Rückel, Bastian & Sölch, Christian & Zöttl, Gregor, 2021. "The impact of market design on transmission and generation investment in electricity markets," Energy Economics, Elsevier, vol. 93(C).
    8. 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.
    9. Makpal Assembayeva & Jonas Egerer & Roman Mendelevitch & Nurkhat Zhakiyev, 2017. "A Spatial Electricity Market Model for the Power System of Kazakhstan," Discussion Papers of DIW Berlin 1659, DIW Berlin, German Institute for Economic Research.
    10. Friedrich Kunz and Alexander Zerrahn, 2016. "Coordinating Cross-Country Congestion Management: Evidence from Central Europe," The Energy Journal, International Association for Energy Economics, vol. 0(Sustainab).
    11. Roman Mendelevitch & Pao-Yu Oei, 2015. "The Impact of Policy Measures on Future Power Generation Portfolio and Infrastructure: A Combined Electricity and CCTS Investment and Dispatch Model (ELCO)," Discussion Papers of DIW Berlin 1521, DIW Berlin, German Institute for Economic Research.
    12. Zerrahn, Alexander, 2017. "Wind Power and Externalities," Ecological Economics, Elsevier, vol. 141(C), pages 245-260.
    13. Horn, Henrik & Tangerås, Thomas, 2021. "National Transmission System Operators in an International Electricity Market," CEPR Discussion Papers 16289, C.E.P.R. Discussion Papers.
    14. Janda, Karel & Málek, Jan & Rečka, Lukáš, 2017. "Influence of renewable energy sources on transmission networks in Central Europe," Energy Policy, Elsevier, vol. 108(C), pages 524-537.
    15. Grimm, Veronika & Rückel, Bastian & Sölch, Christian & Zöttl, Gregor, 2019. "Regionally differentiated network fees to affect incentives for generation investment," Energy, Elsevier, vol. 177(C), pages 487-502.
    16. Herrera, Milton M. & Dyner, Isaac & Cosenz, Federico, 2020. "Benefits from energy policy synchronisation of Brazil’s North-Northeast interconnection," Renewable Energy, Elsevier, vol. 162(C), pages 427-437.
    17. Alexander Zerrahn & Daniel Huppmann, 2017. "Network Expansion to Mitigate Market Power," Networks and Spatial Economics, Springer, vol. 17(2), pages 611-644, June.
    18. Staudt, Philipp & Schmidt, Marc & Gärttner, Johannes & Weinhardt, Christof, 2018. "A decentralized approach towards resolving transmission grid congestion in Germany using vehicle-to-grid technology," Applied Energy, Elsevier, vol. 230(C), pages 1435-1446.
    19. Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Chen, Fu & Li, Weidong, 2018. "Hydropower curtailment in Yunnan Province, southwestern China: Constraint analysis and suggestions," Renewable Energy, Elsevier, vol. 121(C), pages 700-711.
    20. Karel Janda & Jan Málek & Lukáš Rečka, 2017. "Vliv obnovitelných zdrojů na českou soustavu přenosu elektřiny [The Impact of Renewable Energy Sources on the Czech Electricity Transmission System]," Politická ekonomie, Prague University of Economics and Business, vol. 2017(6), pages 728-750.
    21. Voswinkel, Simon & Höckner, Jonas & Khalid, Abuzar & Weber, Christoph, 2022. "Sharing congestion management costs among system operators using the Shapley value," Applied Energy, Elsevier, vol. 317(C).

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