IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i15p2957-d253606.html
   My bibliography  Save this article

The Uncertain Bidder Pays Principle and Its Implementation in a Simple Integrated Portfolio-Bidding Energy-Reserve Market Model

Author

Listed:
  • Dávid Csercsik

    (Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, 1083 Budapest, Práter str. 50/A, Hungary)

  • Ádám Sleisz

    (Department of Electric Power Engineering, Budapest University of Technology and Economics, 1111 Budapest, Egry J. u. 18., Hungary)

  • Péter Márk Sőrés

    (Department of Electric Power Engineering, Budapest University of Technology and Economics, 1111 Budapest, Egry J. u. 18., Hungary)

Abstract

One reason for the allocation of reserves in electricity markets is the uncertainty of demand and supply. If the bias of the generation portfolio shifts from controllable generators to renewable sources with significantly higher uncertainty, it is natural to assume that more reserve has to be allocated. The price of reserve allocation in European models is dominantly paid by the independent system operator in the form of long-term paid reserve capacities and reserve demand bids submitted to various reserve markets. However, if we consider a scenario where the significant part of generation is allocated in day-ahead auctions, the power mix is not known in advance, so the required reserves can not be efficiently curtailed for the ratio of renewables. In the current paper we analyze an integrated European-type, portfolio-bidding energy-reserve market model, which aims to (at least partially) put the burden of reserve allocation costs to the uncertain energy bidders who are partially responsible for the amount of reserves needed. The proposed method in addition proposes a more dynamic and adaptive reserve curtailment method compared to the current practice, while it is formulated in a computationally efficient way.

Suggested Citation

  • Dávid Csercsik & Ádám Sleisz & Péter Márk Sőrés, 2019. "The Uncertain Bidder Pays Principle and Its Implementation in a Simple Integrated Portfolio-Bidding Energy-Reserve Market Model," Energies, MDPI, vol. 12(15), pages 1-25, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2957-:d:253606
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/15/2957/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/15/2957/
    Download Restriction: no
    ---><---

    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. Strbac, Goran & Kirschen, Daniel S., 2000. "Who Should Pay for Reserve?," The Electricity Journal, Elsevier, vol. 13(8), pages 32-37, October.
    3. Meeus, Leonardo & Verhaegen, Karolien & Belmans, Ronnie, 2009. "Block order restrictions in combinatorial electric energy auctions," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1202-1206, August.
    4. Madani, Mehdi & Van Vyve, Mathieu, 2018. "Revisiting minimum profit conditions in uniform price day-ahead electricity auctions," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1072-1085.
    5. Zhenya Ji & Xueliang Huang & Changfu Xu & Houtao Sun, 2016. "Accelerated Model Predictive Control for Electric Vehicle Integrated Microgrid Energy Management: A Hybrid Robust and Stochastic Approach," Energies, MDPI, vol. 9(11), pages 1-18, November.
    6. Jorge Arias & Maria Calle & Daniel Turizo & Javier Guerrero & John E. Candelo-Becerra, 2019. "Historical Load Balance in Distribution Systems Using the Branch and Bound Algorithm," Energies, MDPI, vol. 12(7), pages 1-14, March.
    7. Raineri, R. & Rios, S. & Schiele, D., 2006. "Technical and economic aspects of ancillary services markets in the electric power industry: an international comparison," Energy Policy, Elsevier, vol. 34(13), pages 1540-1555, September.
    8. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    9. 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).
    10. Seyedeh Narjes Fallah & Mehdi Ganjkhani & Shahaboddin Shamshirband & Kwok-wing Chau, 2019. "Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview," Energies, MDPI, vol. 12(3), pages 1-21, January.
    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. Divényi, Dániel & Polgári, Beáta & Sleisz, Ádám & Sőrés, Péter & Raisz, Dávid, 2021. "Investigating minimum income condition orders on European power exchanges: Controversial properties and enhancement proposals," Applied Energy, Elsevier, vol. 281(C).
    2. Ádám Sleisz & Dániel Divényi & Beáta Polgári & Péter Sőrés & Dávid Raisz, 2022. "A Novel Cost Allocation Mechanism for Local Flexibility in the Power System with Partial Disintermediation," Energies, MDPI, vol. 15(22), pages 1-18, November.

    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. Csercsik, Dávid, 2021. "Strategic bidding via the interplay of minimum income condition orders in day-ahead power exchanges," Energy Economics, Elsevier, vol. 95(C).
    2. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "Incorporating unit commitment aspects to the European electricity markets algorithm: An optimization model for the joint clearing of energy and reserve markets," Applied Energy, Elsevier, vol. 231(C), pages 235-258.
    3. Mehdi Madani & Mathieu Van Vyve, 2017. "A MIP framework for non-convex uniform price day-ahead electricity auctions," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 263-284, March.
    4. Kursad Derinkuyu & Fehmi Tanrisever & Nermin Kurt & Gokhan Ceyhan, 2020. "Optimizing Day-Ahead Electricity Market Prices: Increasing the Total Surplus for Energy Exchange Istanbul," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 700-716, July.
    5. 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.
    6. Abhishek Ray & Mario Ventresca & Karthik Kannan, 2021. "A Graph-Based Ant Algorithm for the Winner Determination Problem in Combinatorial Auctions," Information Systems Research, INFORMS, vol. 32(4), pages 1099-1114, December.
    7. Madani, M. & Van Vyve, M., 2015. "A MIP framework for non-convex uniform price day-ahead electricity auctions," LIDAM Discussion Papers CORE 2015017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. D'avid Csercsik, 2020. "Strategic bidding via the interplay of minimum income condition orders in day-ahead power exchanges," Papers 2012.07789, arXiv.org.
    9. 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.
    10. Ceyhan, Gökhan & Köksalan, Murat & Lokman, Banu, 2022. "Extensions for Benders cuts and new valid inequalities for solving the European day-ahead electricity market clearing problem efficiently," European Journal of Operational Research, Elsevier, vol. 300(2), pages 713-726.
    11. Tanrisever, Fehmi & Derinkuyu, Kursad & Jongen, Geert, 2015. "Organization and functioning of liberalized electricity markets: An overview of the Dutch market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1363-1374.
    12. Nermin Elif Kurt & H. Bahadir Sahin & Kurc{s}ad Derinkuyu, 2018. "An Adaptive Tabu Search Algorithm for Market Clearing Problem in Turkish Day-Ahead Market," Papers 1809.10554, arXiv.org.
    13. Han, Jinil & Papavasiliou, Anthony, 2015. "Congestion management through topological corrections: A case study of Central Western Europe," Energy Policy, Elsevier, vol. 86(C), pages 470-482.
    14. Divényi, Dániel & Polgári, Beáta & Sleisz, Ádám & Sőrés, Péter & Raisz, Dávid, 2021. "Investigating minimum income condition orders on European power exchanges: Controversial properties and enhancement proposals," Applied Energy, Elsevier, vol. 281(C).
    15. 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.
    16. Gokhan Ceyhan & Nermin Elif Kurt & H. Bahadir Sahin & Kurc{s}ad Derinkuyu, 2017. "Empirical comparison of three models for determining market clearing prices in Turkish day-ahead electricity market," Papers 1712.00235, arXiv.org.
    17. Nikolaos Koltsaklis & Athanasios Dagoumas, 2018. "Policy Implications of Power Exchanges on Operational Scheduling: Evaluating EUPHEMIA’s Market Products in Case of Greece," Energies, MDPI, vol. 11(10), pages 1-26, October.
    18. Jérôme De Boeck & Luce Brotcorne & Bernard Fortz, 2022. "Strategic bidding in price coupled regions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(3), pages 365-407, June.
    19. Sofiane Aboura, 2014. "When the U.S. Stock Market Becomes Extreme?," Risks, MDPI, vol. 2(2), pages 1-15, May.
    20. Winter, Peter, 2007. "Managerial Risk Accounting and Control – A German perspective," MPRA Paper 8185, University Library of Munich, Germany.

    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:gam:jeners:v:12:y:2019:i:15:p:2957-:d:253606. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.