IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v240y2019icp251-264.html
   My bibliography  Save this article

Extended opportunity cost model to find near equilibrium electricity prices under non-convexities

Author

Listed:
  • Shavandi, Hassan
  • Pirnia, Mehrdad
  • Fuller, J. David

Abstract

This paper finds near equilibrium prices for electricity markets with non-convexities due to binary variables, in order to reduce the market participants’ opportunity costs, such as generators’ unrecovered costs. The opportunity cost is defined as the difference between the profit when the instructions of the market operator are followed and when the market participants can freely make their own decisions based on the market prices. We use the minimum complementarity approximation to the minimum total opportunity cost model, from previous research, with tests on a much more realistic unit commitment model than in previous research, including features such as reserve requirements, ramping constraints, and minimum-up and -down times. The developed model incorporates flexible price-responsive demand, as in previous research, but since not all demand is price responsive, we consider the more realistic case that total demand is a mixture of fixed and flexible. Another improvement over previous minimum total opportunity cost research is computational: whereas the previous research had nonconvex terms among the objective function’s continuous variables, we convert the objective to an equivalent form that contains only linear and convex quadratic terms in the continuous variables, thus allowing for efficient optimization by CPLEX.

Suggested Citation

  • Shavandi, Hassan & Pirnia, Mehrdad & Fuller, J. David, 2019. "Extended opportunity cost model to find near equilibrium electricity prices under non-convexities," Applied Energy, Elsevier, vol. 240(C), pages 251-264.
  • Handle: RePEc:eee:appene:v:240:y:2019:i:c:p:251-264
    DOI: 10.1016/j.apenergy.2019.02.059
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191930354X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.02.059?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. Steven Gabriel & Sauleh Siddiqui & Antonio Conejo & Carlos Ruiz, 2013. "Solving Discretely-Constrained Nash–Cournot Games with an Application to Power Markets," Networks and Spatial Economics, Springer, vol. 13(3), pages 307-326, September.
    2. Steven A. Gabriel & Antonio J. Conejo & J. David Fuller & Benjamin F. Hobbs & Carlos Ruiz, 2013. "Complementarity Modeling in Energy Markets," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4419-6123-5, April.
    3. Gregory Steeger & Steffen Rebennack, 2015. "Strategic bidding for multiple price-maker hydroelectric producers," IISE Transactions, Taylor & Francis Journals, vol. 47(9), pages 1013-1031, September.
    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. Wang, Yong & Li, Lin, 2015. "Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities," Applied Energy, Elsevier, vol. 149(C), pages 89-103.
    6. Herbert Scarf, 1994. "The Allocation of Resources in the Presence of Indivisibilities," Journal of Economic Perspectives, American Economic Association, vol. 8(4), pages 111-128, Fall.
    7. David Fuller, J. & Çelebi, Emre, 2017. "Alternative models for markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 261(2), pages 436-449.
    8. Zoltowska, Izabela, 2016. "Demand shifting bids in energy auction with non-convexities and transmission constraints," Energy Economics, Elsevier, vol. 53(C), pages 17-27.
    9. Huppmann, Daniel & Siddiqui, Sauleh, 2018. "An exact solution method for binary equilibrium problems with compensation and the power market uplift problem," European Journal of Operational Research, Elsevier, vol. 266(2), pages 622-638.
    10. Bjørndal, Mette & Jörnsten, Kurt, 2008. "Equilibrium prices supported by dual price functions in markets with non-convexities," European Journal of Operational Research, Elsevier, vol. 190(3), pages 768-789, November.
    11. 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.
    12. Araoz, Veronica & Jörnsten, Kurt, 2011. "Semi-Lagrangean approach for price discovery in markets with non-convexities," European Journal of Operational Research, Elsevier, vol. 214(2), pages 411-417, October.
    13. George Liberopoulos & Panagiotis Andrianesis, 2016. "Critical Review of Pricing Schemes in Markets with Non-Convex Costs," Operations Research, INFORMS, vol. 64(1), pages 17-31, February.
    14. Yiduo Zhan & Qipeng P. Zheng, 2018. "A multistage decision-dependent stochastic bilevel programming approach for power generation investment expansion planning," IISE Transactions, Taylor & Francis Journals, vol. 50(8), pages 720-734, August.
    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. Liu, Shuo & Yang, Zhifang & Xia, Qing & Lin, Wei & Shi, Lianjun & Zeng, Dan, 2020. "Power trading region considering long-term contract for interconnected power networks," Applied Energy, Elsevier, vol. 261(C).
    2. Vadim Borokhov, 2022. "Utilizing the redundant constraints for the uplift payment elimination," Operational Research, Springer, vol. 22(2), pages 1377-1402, April.

    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. Hassan Shavandi & Mehrdad Pirnia & J. David Fuller, 2018. "Extended opportunity cost model to find near equilibrium electricity prices under non-convexities," Papers 1809.09734, arXiv.org.
    2. David Fuller, J. & Çelebi, Emre, 2017. "Alternative models for markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 261(2), pages 436-449.
    3. Vadim Borokhov, 2022. "Utilizing the redundant constraints for the uplift payment elimination," Operational Research, Springer, vol. 22(2), pages 1377-1402, April.
    4. Kuang, Xiaolong & Lamadrid, Alberto J. & Zuluaga, Luis F., 2019. "Pricing in non-convex markets with quadratic deliverability costs," Energy Economics, Elsevier, vol. 80(C), pages 123-131.
    5. Hacopian Dolatabadi, Sarineh & Latify, Mohammad Amin & Karshenas, Hamidreza & Sharifi, Alimorad, 2022. "On pricing issues in electricity markets in the presence of externalities," Energy, Elsevier, vol. 246(C).
    6. Löschenbrand, Markus, 2020. "Finding multiple Nash equilibria via machine learning-supported Gröbner bases," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1178-1189.
    7. Vazquez, Carlos & Hallack, Michelle & Vazquez, Miguel, 2017. "Price computation in electricity auctions with complex rules: An analysis of investment signals," Energy Policy, Elsevier, vol. 105(C), pages 550-561.
    8. George Liberopoulos & Panagiotis Andrianesis, 2016. "Critical Review of Pricing Schemes in Markets with Non-Convex Costs," Operations Research, INFORMS, vol. 64(1), pages 17-31, February.
    9. Navid Azizan & Yu Su & Krishnamurthy Dvijotham & Adam Wierman, 2020. "Optimal Pricing in Markets with Nonconvex Costs," Operations Research, INFORMS, vol. 68(2), pages 480-496, March.
    10. Wang, Yi & Yang, Zhifang & Yu, Juan & Liu, Sixu, 2023. "Pricing in non-convex electricity markets with flexible trade-off of pricing properties," Energy, Elsevier, vol. 274(C).
    11. Dimitri J. Papageorgiou & Francisco Trespalacios & Stuart Harwood, 2021. "A Note on Solving Discretely-Constrained Nash-Cournot Games via Complementarity," Networks and Spatial Economics, Springer, vol. 21(2), pages 325-330, June.
    12. Martin Bichler & Johannes Knörr & Felipe Maldonado, 2023. "Pricing in Nonconvex Markets: How to Price Electricity in the Presence of Demand Response," Information Systems Research, INFORMS, vol. 34(2), pages 652-675, June.
    13. 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.
    14. Xin Shi & Alberto J. Lamadrid L. & Luis F. Zuluaga, 2021. "Revenue Adequate Prices for Chance-Constrained Electricity Markets with Variable Renewable Energy Sources," Papers 2105.01233, arXiv.org.
    15. Holmberg, Pär & Tangerås, Thomas & Ahlqvist, Victor, 2018. "Central- versus Self-Dispatch in Electricity Markets," Working Paper Series 1257, Research Institute of Industrial Economics, revised 27 Mar 2019.
    16. Martin Bichler & Hans Ulrich Buhl & Johannes Knörr & Felipe Maldonado & Paul Schott & Stefan Waldherr & Martin Weibelzahl, 2022. "Electricity Markets in a Time of Change: A Call to Arms for Business Research," Schmalenbach Journal of Business Research, Springer, vol. 74(1), pages 77-102, March.
    17. Bobo, Lucien & Mitridati, Lesia & Taylor, Josh A. & Pinson, Pierre & Kazempour, Jalal, 2021. "Price-region bids in electricity markets," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1056-1073.
    18. Mays, Jacob & Morton, David P. & O’Neill, Richard P., 2021. "Investment effects of pricing schemes for non-convex markets," European Journal of Operational Research, Elsevier, vol. 289(2), pages 712-726.
    19. Araoz, Veronica & Jörnsten, Kurt, 2011. "Semi-Lagrangean approach for price discovery in markets with non-convexities," European Journal of Operational Research, Elsevier, vol. 214(2), pages 411-417, October.
    20. Lukas Hümbs & Alexander Martin & Lars Schewe, 2022. "Exploiting complete linear descriptions for decentralized power market problems with integralities," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(3), pages 451-474, June.

    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:appene:v:240:y:2019:i:c:p:251-264. 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: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.