IDEAS home Printed from https://ideas.repec.org/p/hhs/nhhfms/2017_014.html
   My bibliography  Save this paper

Market Power Under Nodal and Zonal Congestion Management Techniques

Author

Listed:
  • Bjørndal, Endre

    (Dept. of Business and Management Science, Norwegian School of Economics)

  • Bjørndal, Mette

    (Dept. of Business and Management Science, Norwegian School of Economics)

  • Rud, Linda

    (Dept. of Business and Management Science, Norwegian School of Economics)

  • Alangi, Somayeh Rahimi

    (Dept. of Business and Management Science, Norwegian School of Economics)

Abstract

Contrary to the common thought that nodal pricing provides more opportunities for a strategic player to exert market power than the zonal model, we show that in the latter one because of the need for re-dispatch or counter-trading, another extra place is created letting more gaming possibilities. Therefore, if proper market power mitigation approaches are not utilized in both day-ahead and re-dispatch markets, then zonal pricing may be more susceptible to market power, especially in zonal model which is based on available transfer capacity (ATC), strategic player's profit and social welfare can be very volatile. In general, the more network constraints are incorporated in day-ahead market (100% in nodal and almost zero in ATC), the more social welfare is attainable. Hence, nodal model is acquitted from the more market power denunciation.

Suggested Citation

  • Bjørndal, Endre & Bjørndal, Mette & Rud, Linda & Alangi, Somayeh Rahimi, 2017. "Market Power Under Nodal and Zonal Congestion Management Techniques," Discussion Papers 2017/14, Norwegian School of Economics, Department of Business and Management Science.
    • Handle: RePEc:hhs:nhhfms:2017_014
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/11250/2464570
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dijk, Justin & Willems, Bert, 2011. "The effect of counter-trading on competition in electricity markets," Energy Policy, Elsevier, vol. 39(3), pages 1764-1773, March.
    2. van Blijswijk, Martti J. & de Vries, Laurens J., 2012. "Evaluating congestion management in the Dutch electricity transmission grid," Energy Policy, Elsevier, vol. 51(C), pages 916-926.
    3. Bjorndal, Mette & Jornsten, Kurt, 2007. "Benefits from coordinating congestion management--The Nordic power market," Energy Policy, Elsevier, vol. 35(3), pages 1978-1991, March.
    4. Pär Holmberg and Ewa Lazarczyk, 2015. "Comparison of congestion management techniques: Nodal, zonal and discriminatory pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    5. OGGIONI, Giorgia & SMEERS, Yves, 2013. "Market failures of market coupling and counter-trading in Europe: an illustrative model based discussion," LIDAM Reprints CORE 2553, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Bjørndal, Endre & Bjørndal, Mette & Midthun, Kjetil & Zakeri, Golbon, 2016. "Congestion Management in a Stochastic Dispatch Model for Electricity Markets," Discussion Papers 2016/12, Norwegian School of Economics, Department of Business and Management Science.
    7. Mette Bjorndal & Kurt Jornsten, 2001. "Zonal Pricing in a Deregulated Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 51-73.
    8. Vincent Rious & Jean-Michel Glachant & Marcelo Saguan & Philippe Dessante & Julio Usaola, 2008. "Assessing Available Transfer Capacity on a Realistic European Network: Impact of Assumptions on Cross-border Exchanges and on Wind Power Generation," Post-Print hal-00324664, HAL.
    9. 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).
    10. Morales, Juan M. & Zugno, Marco & Pineda, Salvador & Pinson, Pierre, 2014. "Electricity market clearing with improved scheduling of stochastic production," European Journal of Operational Research, Elsevier, vol. 235(3), pages 765-774.
    11. Giorgia Oggioni and Yves Smeers, 2012. "Degrees of Coordination in Market Coupling and Counter-Trading," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    12. Ignacio Aravena & Anthony Papavasiliou, 2017. "Renewable energy integration in zonal markets," LIDAM Reprints CORE 2932, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Giorgia Oggioni & Yves Smeers & Elisabetta Allevi & Siegfried Schaible, 2012. "A Generalized Nash Equilibrium Model of Market Coupling in the European Power System," Networks and Spatial Economics, Springer, vol. 12(4), pages 503-560, December.
    14. Vincent Rious & Julio Usaola & Marcelo Saguan & Jean-Michel Glachant & Philippe Dessante, 2008. "Assessing Available Transfer Capacity on a Realistic European Network: Impact of Assumptions on Wind Power Generation," Post-Print hal-00338749, HAL.
    15. R.A. Hakvoort & L.J. De Vries, 2002. "An economic assessment of congestion management methods for electricity transmission networks," Competition and Regulation in Network Industries, Intersentia, vol. 3(4), pages 425-467, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. Ruderer, Dominik & Zöttl, Gregor, 2018. "Transmission pricing and investment incentives," Utilities Policy, Elsevier, vol. 55(C), pages 14-30.
    4. Höckner, Jonas & Voswinkel, Simon & Weber, Christoph, 2020. "Market distortions in flexibility markets caused by renewable subsidies – The case for side payments," Energy Policy, Elsevier, vol. 137(C).
    5. Jonas Höckner & Simon Voswinkel & Christoph Weber, "undated". "Market distortions in flexibility markets caused by renewable subsidies – The case for side payments," EWL Working Papers 1905, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    6. Simshauser, Paul, 2024. "On static vs. dynamic line ratings in renewable energy zones," Energy Economics, Elsevier, vol. 129(C).
    7. Martin Weibelzahl & Alexandra Märtz, 2020. "Optimal storage and transmission investments in a bilevel electricity market model," Annals of Operations Research, Springer, vol. 287(2), pages 911-940, April.
    8. 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.
    9. Paul Simshauser & Farhad Billimoria & Craig Rogers, 2021. "Optimising VRE plant capacity in Renewable Energy Zones," Working Papers EPRG2121, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    10. Ambrosius, M. & Egerer, J. & Grimm, V. & Weijde, A.H. van der, 2020. "Uncertain bidding zone configurations: The role of expectations for transmission and generation capacity expansion," European Journal of Operational Research, Elsevier, vol. 285(1), pages 343-359.
    11. Simshauser, Paul, 2021. "Renewable Energy Zones in Australia's National Electricity Market," Energy Economics, Elsevier, vol. 101(C).
    12. Joachim Bertsch & Simeon Hagspiel & Lisa Just, 2016. "Congestion management in power systems," Journal of Regulatory Economics, Springer, vol. 50(3), pages 290-327, December.
    13. Blázquez De Paz, Mario, 2017. "Production or Transmission Investments? A Comparative Analysis," Working Paper Series 1158, Research Institute of Industrial Economics.
    14. Blázquez de Paz, Mario, 2019. "Redispatch in Zonal Pricing Electricity Markets," Working Paper Series 1278, Research Institute of Industrial Economics.
    15. 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.
    16. Felten, Björn & Osinski, Paul & Felling, Tim & Weber, Christoph, 2021. "The flow-based market coupling domain - Why we can't get it right," Utilities Policy, Elsevier, vol. 70(C).
    17. Sarfati, Mahir & Hesamzadeh, Mohammed Reza & Holmberg, Pär, 2019. "Production Efficiency of Nodal and Zonal Pricing in Imperfectly Competitive Electricity Markets," Working Paper Series 1264, Research Institute of Industrial Economics.
    18. Sarfati, Mahir & Hesamzadeh, Mohammad Reza & Holmberg, Pär, 2018. "Increase-Decrease Game under Imperfect Competition in Two-stage Zonal Power Markets –​ Part I: Concept Analysis," Working Paper Series 1253, Research Institute of Industrial Economics.
    19. Bertsch, Joachim & Hagspiel, Simeon & Just, Lisa, 2016. "Congestion management in power systems - Long-term modeling framework and large-scale application," EWI Working Papers 2015-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    20. M. Sarfati & M.R. Hesamzadeh & P. Holmberg, 2018. "Increase-Decrease Game under Imperfect Competition in Two-stage Zonal Power Markets – Part I: Concept Analysis," Working Papers EPRG 1837, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.

    More about this item

    Keywords

    Market design; congestion management; available transfer capacity (ATC); market power; exibility cost of re-dispatch or counter-trading;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:nhhfms:2017_014. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Stein Fossen (email available below). General contact details of provider: https://edirc.repec.org/data/dfnhhno.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.