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New Clearing Model to Mitigate the Non-Convexity in European Day-ahead Electricity Market

Author

Listed:
  • Le Hong Lam

    (Faculty of Electrical Engineering, The University of Danang—University of Science and Technology, 54 Nguyen Luong Bang, Danang 550000, Vietnam)

  • Valentin Ilea

    (Department of Energy, Politecnico di Milano, Via LaMasa, 34, 20156 Milano, Italy)

  • Cristian Bovo

    (Department of Energy, Politecnico di Milano, Via LaMasa, 34, 20156 Milano, Italy)

Abstract

Nowadays, the payment scheme of European Day-Ahead Market is based on the market clearing price by running the Pan-European Hybrid Electricity Market Integration Algorithm. However, this conventional payment scheme is challenging because of the non-convexity and the short computation time requirement. Thus, the aim of this work is to propose a new clearing model in order to mitigate this challenge. The model is based on make-whole payment mechanism and it includes two major steps: (i) maximizing social welfare and (ii) achieving a Walrasian equilibrium by the “minimum-uplift approach”. The proposed model is validated and investigated by two case studies: one is an artificially created Day-Ahead Market session containing all type of bids encountered in Europe and containing a very large number of bids to stress the algorithm and the other is a reduced, but realistic, model of European market where real data from February to December of 2017 were considered. The tests show a consistent improvement of the numerical performances of the proposed model with respect to the conventional one while the economic performance is not altered, but is slightly improved. Moreover, because the tests are based on real data during a long period of time, the results show that proposed model is very promising for the real application.

Suggested Citation

  • Le Hong Lam & Valentin Ilea & Cristian Bovo, 2020. "New Clearing Model to Mitigate the Non-Convexity in European Day-ahead Electricity Market," Energies, MDPI, vol. 13(18), pages 1-28, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4716-:d:411566
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    References listed on IDEAS

    as
    1. Madani, Mehdi & Van Vyve, Mathieu, 2015. "Computationally efficient MIP formulation and algorithms for European day-ahead electricity market auctions," European Journal of Operational Research, Elsevier, vol. 242(2), pages 580-593.
    2. Iacopo Savelli & Bertrand Corn'elusse & Antonio Giannitrapani & Simone Paoletti & Antonio Vicino, 2017. "A New Approach to Electricity Market Clearing With Uniform Purchase Price and Curtailable Block Orders," Papers 1711.07731, arXiv.org, revised Jun 2018.
    3. VAN VYVE, Mathieu, 2011. "Linear prices for non-convex electricity markets: models and algorithms," LIDAM Discussion Papers CORE 2011050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. O'Neill, Richard P. & Sotkiewicz, Paul M. & Hobbs, Benjamin F. & Rothkopf, Michael H. & Stewart, William R., 2005. "Efficient market-clearing prices in markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 164(1), pages 269-285, July.
    5. Le, Hong Lam & Ilea, Valentin & Bovo, Cristian, 2019. "Integrated European intra-day electricity market: Rules, modeling and analysis," Applied Energy, Elsevier, vol. 238(C), pages 258-273.
    6. Savelli, Iacopo & Cornélusse, Bertrand & Giannitrapani, Antonio & Paoletti, Simone & Vicino, Antonio, 2018. "A new approach to electricity market clearing with uniform purchase price and curtailable block orders," Applied Energy, Elsevier, vol. 226(C), pages 618-630.
    7. Mehdi MADANI & Mathieu VAN VYVE, 2015. "Computationally efficient MIP formulation and algorithms for European day-ahead electricity market auctions," LIDAM Reprints CORE 2808, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. Samuli Honkapuro & Jasmin Jaanto & Salla Annala, 2023. "A Systematic Review of European Electricity Market Design Options," Energies, MDPI, vol. 16(9), pages 1-26, April.

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