IDEAS home Printed from https://ideas.repec.org/a/eee/juipol/v79y2022ics0957178722001205.html
   My bibliography  Save this article

An integrated model for electricity market coupling simulations: Evidence from the European power market crossroad

Author

Listed:
  • Halužan, Marko
  • Verbič, Miroslav
  • Zorić, Jelena

Abstract

Motivated by the project of European Power Exchanges to develop a single price-coupling solution to calculate electricity prices across Europe that respects the cross-border capacity constraints on a day-ahead basis, we empirically examine and quantify market inefficiencies in non-coupled day-ahead electricity markets. These result from inefficient cross-border capacity allocation and its underlying effect on the market clearing prices. Efficient cross-border capacity allocation and new market clearing prices are simulated using a social welfare maximisation algorithm for the capacity of relevant network elements, whereas the order book generation process is reproduced by the econometrically estimated supply price elasticity functions. The estimated vector autoregression model and the underlying impulse response functions examine price shock transmission under different market regimes. The market coupling process is simulated on the historical non-coupled day-ahead market realisations at the junction of three regional power markets: Central Western Europe, Northern Italian, and South Eastern European markets. Simulation results confirm steady, efficient cross-border capacity utilisation, reduced price variance, improved overall price convergence and amplified price shock transmission in coupled electricity markets. Furthermore, in the simulated period, we have estimated an increase in the overall suppliers' and consumers’ surplus of almost EUR 16 million. The proposed simulation framework is a clear choice for applied simulation in coupled day-ahead electricity markets, offering valuable visual insights into the cross-border capacity allocation and its implications on electricity prices.

Suggested Citation

  • Halužan, Marko & Verbič, Miroslav & Zorić, Jelena, 2022. "An integrated model for electricity market coupling simulations: Evidence from the European power market crossroad," Utilities Policy, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:juipol:v:79:y:2022:i:c:s0957178722001205
    DOI: 10.1016/j.jup.2022.101456
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0957178722001205
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jup.2022.101456?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cyril Martin de Lagarde & Frédéric Lantz, 2018. "How renewable production depresses electricity prices: Evidence from the German market," Post-Print hal-01985024, HAL.
    2. Parisio, Lucia & Bosco, Bruno, 2008. "Electricity prices and cross-border trade: Volume and strategy effects," Energy Economics, Elsevier, vol. 30(4), pages 1760-1775, July.
    3. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    4. Li, Wei & Becker, Denis Mike, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Energy, Elsevier, vol. 237(C).
    5. Kiesel, Rüdiger & Kusterman, Michael, 2016. "Structural models for coupled electricity markets," Journal of Commodity Markets, Elsevier, vol. 3(1), pages 16-38.
    6. Keles, Dogan & Genoese, Massimo & Möst, Dominik & Ortlieb, Sebastian & Fichtner, Wolf, 2013. "A combined modeling approach for wind power feed-in and electricity spot prices," Energy Policy, Elsevier, vol. 59(C), pages 213-225.
    7. Meeus, Leonardo, 2011. "Implicit auctioning on the Kontek Cable: Third time lucky?," Energy Economics, Elsevier, vol. 33(3), pages 413-418, May.
    8. Abadie, Luis María & Chamorro, José Manuel, 2021. "Evaluation of a cross-border electricity interconnection: The case of Spain-France," Energy, Elsevier, vol. 233(C).
    9. Hellwig, Michael & Schober, Dominik & Woll, Oliver, 2020. "Measuring market integration and estimating policy impacts on the Swiss electricity market," Energy Economics, Elsevier, vol. 86(C).
    10. Lago, Jesus & De Ridder, Fjo & Vrancx, Peter & De Schutter, Bart, 2018. "Forecasting day-ahead electricity prices in Europe: The importance of considering market integration," Applied Energy, Elsevier, vol. 211(C), pages 890-903.
    11. Simona Bigerna, Carlo Andrea Bollino and Paolo Polinori, 2016. "Renewable Energy and Market Power in the Italian Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Bollino-M).
    12. Hong, Tao & Pinson, Pierre & Fan, Shu & Zareipour, Hamidreza & Troccoli, Alberto & Hyndman, Rob J., 2016. "Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond," International Journal of Forecasting, Elsevier, vol. 32(3), pages 896-913.
    13. Dagoumas, Athanasios S. & Koltsaklis, Nikolasos E. & Panapakidis, Ioannis P., 2017. "An integrated model for risk management in electricity trade," Energy, Elsevier, vol. 124(C), pages 350-363.
    14. Rafal Weron & Adam Misiorek, 2005. "Forecasting Spot Electricity Prices With Time Series Models," Econometrics 0504001, University Library of Munich, Germany.
    15. Halužan, Marko & Verbič, Miroslav & Zorić, Jelena, 2020. "Performance of alternative electricity price forecasting methods: Findings from the Greek and Hungarian power exchanges," Applied Energy, Elsevier, vol. 277(C).
    16. Martin de Lagarde, Cyril & Lantz, Frédéric, 2018. "How renewable production depresses electricity prices: Evidence from the German market," Energy Policy, Elsevier, vol. 117(C), pages 263-277.
    17. Andreas Ehrenmann & Karsten Neuhoff, 2009. "A Comparison of Electricity Market Designs in Networks," Operations Research, INFORMS, vol. 57(2), pages 274-286, April.
    18. Zorana Božić & Dušan Dobromirov & Jovana Arsić & Mladen Radišić & Beata Ślusarczyk, 2020. "Power Exchange Prices: Comparison of Volatility in European Markets," Energies, MDPI, vol. 13(21), pages 1-15, October.
    19. Pellini, Elisabetta, 2012. "Measuring the impact of market coupling on the Italian electricity market," Energy Policy, Elsevier, vol. 48(C), pages 322-333.
    20. Cyril Martin de Lagarde & Frédéric Lantz, 2018. "How renewable production depresses electricity prices: Evidence from the German market," Post-Print hal-01986207, HAL.
    21. repec:taf:applec:45:y:2013:i:18:p:2683-2693 is not listed on IDEAS
    22. Ronald Huisman & Mehtap Kili砍, 2013. "A history of European electricity day-ahead prices," Applied Economics, Taylor & Francis Journals, vol. 45(18), pages 2683-2693, June.
    23. Luigi Grossi & Sven Heim & Kai Hüschelrath & Michael Waterson, 2018. "Electricity market integration and the impact of unilateral policy reforms," Oxford Economic Papers, Oxford University Press, vol. 70(3), pages 799-820.
    24. Lijesen, Mark G., 2007. "The real-time price elasticity of electricity," Energy Economics, Elsevier, vol. 29(2), pages 249-258, March.
    25. repec:bla:jfinan:v:59:y:2004:i:4:p:1877-1900 is not listed on IDEAS
    26. De Vany, Arthur S & Walls, W David, 1999. "Price Dynamics in a Network of Decentralized Power Markets," Journal of Regulatory Economics, Springer, vol. 15(2), pages 123-140, March.
    27. Wei Li & Denis Mike Becker, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Papers 2101.05249, arXiv.org, revised Jul 2021.
    Full references (including those not matched with items on IDEAS)

    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. Halužan, Marko & Verbič, Miroslav & Zorić, Jelena, 2020. "Performance of alternative electricity price forecasting methods: Findings from the Greek and Hungarian power exchanges," Applied Energy, Elsevier, vol. 277(C).
    2. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    3. Renato Fernandes & Isabel Soares, 2022. "Reviewing Explanatory Methodologies of Electricity Markets: An Application to the Iberian Market," Energies, MDPI, vol. 15(14), pages 1-17, July.
    4. Vika Koban, 2017. "The impact of market coupling on Hungarian and Romanian electricity markets: Evidence from the regime-switching model," Energy & Environment, , vol. 28(5-6), pages 621-638, September.
    5. Saez, Yago & Mochon, Asuncion & Corona, Luis & Isasi, Pedro, 2019. "Integration in the European electricity market: A machine learning-based convergence analysis for the Central Western Europe region," Energy Policy, Elsevier, vol. 132(C), pages 549-566.
    6. Panos, Evangelos & Densing, Martin, 2019. "The future developments of the electricity prices in view of the implementation of the Paris Agreements: Will the current trends prevail, or a reversal is ahead?," Energy Economics, Elsevier, vol. 84(C).
    7. Sergio Cantillo-Luna & Ricardo Moreno-Chuquen & Jesus Lopez-Sotelo & David Celeita, 2023. "An Intra-Day Electricity Price Forecasting Based on a Probabilistic Transformer Neural Network Architecture," Energies, MDPI, vol. 16(19), pages 1-24, September.
    8. Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
    9. Janke, Leandro & McDonagh, Shane & Weinrich, Sören & Murphy, Jerry & Nilsson, Daniel & Hansson, Per-Anders & Nordberg, Åke, 2020. "Optimizing power-to-H2 participation in the Nord Pool electricity market: Effects of different bidding strategies on plant operation," Renewable Energy, Elsevier, vol. 156(C), pages 820-836.
    10. Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, vol. 14(11), pages 1-17, June.
    11. Komorowska, Aleksandra & Benalcazar, Pablo & Kaszyński, Przemysław & Kamiński, Jacek, 2020. "Economic consequences of a capacity market implementation: The case of Poland," Energy Policy, Elsevier, vol. 144(C).
    12. Wilkinson, Sam & Maticka, Martin J. & Liu, Yue & John, Michele, 2021. "The duck curve in a drying pond: The impact of rooftop PV on the Western Australian electricity market transition," Utilities Policy, Elsevier, vol. 71(C).
    13. Comincioli, Nicola & Vergalli, Sergio, 2020. "Effects of Carbon Tax on Electricity Price Volatility: Empirical Evidences from the Australian Market," 2030 Agenda 305205, Fondazione Eni Enrico Mattei (FEEM).
    14. Luigi De Paoli & Elena Fumagalli, 2013. "Estimating welfare losses and gains in explicit auctions for power trade: an application to the Italian case," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2013(2), pages 153-181.
    15. Rinne, Sonja, 2024. "Estimating the merit-order effect using coarsened exact matching: Reconciling theory with the empirical results to improve policy implications," Energy Policy, Elsevier, vol. 185(C).
    16. Samarth Kumar & David Schönheit & Matthew Schmidt & Dominik Möst, 2019. "Parsing the Effects of Wind and Solar Generation on the German Electricity Trade Surplus," Energies, MDPI, vol. 12(18), pages 1-17, September.
    17. Macedo, Daniela Pereira & Marques, António Cardoso & Damette, Olivier, 2022. "The role of electricity flows and renewable electricity production in the behaviour of electricity prices in Spain," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 885-900.
    18. Macedo, Daniela Pereira & Marques, António Cardoso & Damette, Olivier, 2020. "The impact of the integration of renewable energy sources in the electricity price formation: is the Merit-Order Effect occurring in Portugal?," Utilities Policy, Elsevier, vol. 66(C).
    19. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    20. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).

    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:eee:juipol:v:79:y:2022:i:c:s0957178722001205. 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: Catherine Liu (email available below). General contact details of provider: https://www.sciencedirect.com/journal/utilities-policy .

    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.