IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v47y2026i1p165-192.html

Participation of Variable Renewable Generators in Forward Markets: A Game-Theoretic Analysis

Author

Listed:
  • Rui Huang
  • Qinglong Gou
  • Juzhi Zhang

Abstract

This paper addresses the pressing question of whether renewable generators (RGs) should participate in forward markets, traditionally used by conventional generators (CGs) to hedge against spot market risks. We develop a stylized game-theoretical model that captures hybrid generation technologies, demand and supply uncertainties, and increasing demand-side engagement in today’s electricity markets. Our analysis reveals that the forward participation of prioritized RGs intensifies competition in the forward markets but inadvertently bolsters CGs’ market power in the spot markets. This dynamic may create a “one wins, many lose†outcome, where RGs benefit at the expense of consumer surplus, social welfare, and other stakeholders. Additionally, priority dispatch incentivizes RGs to contract more aggressively than CGs. Although allowing RGs to withhold output can mitigate these adverse effects, numerical results indicate that priority dispatch ultimately yields greater social benefits. Sensitivity analysis further shows that RGs’ forward participation can reshape how market factors influence market equilibrium. JEL Classification: C72 - Noncooperative Games; D43 - Market Structure, Pricing, and Design: Oligopoly and Other Forms of Market Imperfection; Q41 - Energy: Demand and Supply; Prices; Q48 - Energy: Government Policy

Suggested Citation

  • Rui Huang & Qinglong Gou & Juzhi Zhang, 2026. "Participation of Variable Renewable Generators in Forward Markets: A Game-Theoretic Analysis," The Energy Journal, , vol. 47(1), pages 165-192, January.
    • Handle: RePEc:sae:enejou:v:47:y:2026:i:1:p:165-192
    DOI: 10.1177/01956574251368288
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/01956574251368288
    Download Restriction: no
    File URL: https://libkey.io/10.1177/01956574251368288?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
    ---><---

    References listed on IDEAS

    as
    1. Sam Aflaki & Serguei Netessine, 2017. "Strategic Investment in Renewable Energy Sources: The Effect of Supply Intermittency," Manufacturing & Service Operations Management, INFORMS, vol. 19(3), pages 489-507, July.
    2. Owen Q. Wu & Roman Kapuscinski & Santhosh Suresh, 2023. "On the Distributed Energy Storage Investment and Operations," Manufacturing & Service Operations Management, INFORMS, vol. 25(6), pages 2277-2297, November.
    3. Morales, Juan M. & Pineda, Salvador, 2017. "On the inefficiency of the merit order in forward electricity markets with uncertain supply," European Journal of Operational Research, Elsevier, vol. 261(2), pages 789-799.
    4. Yashar Ghiassi-Farrokhfal & Rodrigo Belo & Mohammad Reza Hesamzadeh & Derek Bunn, 2023. "Optimal Electricity Imbalance Pricing for the Emerging Penetration of Renewable and Low-Cost Generators," Manufacturing & Service Operations Management, INFORMS, vol. 25(5), pages 1966-1983, September.
    5. Nur Sunar & John R. Birge, 2019. "Strategic Commitment to a Production Schedule with Uncertain Supply and Demand: Renewable Energy in Day-Ahead Electricity Markets," Management Science, INFORMS, vol. 65(2), pages 714-734, February.
    6. Siddiqui, Afzal S. & Tanaka, Makoto & Chen, Yihsu, 2019. "Sustainable transmission planning in imperfectly competitive electricity industries: Balancing economic and environmental outcomes," European Journal of Operational Research, Elsevier, vol. 275(1), pages 208-223.
    7. Paul L Joskow, 2019. "Challenges for wholesale electricity markets with intermittent renewable generation at scale: the US experience," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 35(2), pages 291-331.
    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. Fariba F. Mamaghani & Metin Çakanyildirim, 2024. "Harvesting Solar Power Foments Prices in a Vicious Cycle: Breaking the Cycle with Price Mechanisms," Operations Research, INFORMS, vol. 72(4), pages 1505-1525, July.
    2. Mier, Mathias, 2021. "Efficient pricing of electricity revisited," Energy Economics, Elsevier, vol. 104(C).
    3. Sankaranarayanan, Sriram & Feijoo, Felipe & Mukherjee, Saral, 2025. "The environmental value of an owned agile power source," Energy, Elsevier, vol. 334(C).
    4. Wang, Xianjia & Tianrun, He & Zhang, Ling, 2025. "Wind energy use under electricity supply guarantee rates: The impact of two incentive policies," Energy, Elsevier, vol. 322(C).
    5. Rui, Zhaobiao & Peng, Weicai & Qin, Ximei & Wang, Jun, 2023. "Assessing carbon cap-and-trade policies on hybrid renewable energy investments: Implications for pricing and capacity decisions," Resources Policy, Elsevier, vol. 86(PA).
    6. Volodymyr Babich & Ruben Lobel & Şafak Yücel, 2020. "Promoting Solar Panel Investments: Feed-in-Tariff vs. Tax-Rebate Policies," Manufacturing & Service Operations Management, INFORMS, vol. 22(6), pages 1148-1164, November.
    7. Panos Kouvelis & Hirofumi Matsuo & Yixuan Xiao & Quan Yuan, 2023. "Long‐term service agreement in electricity supply chain with renewable energy penetration," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1830-1845, June.
    8. Zuguang Gao & Khaled Alshehri & John R. Birge, 2024. "Aggregating Distributed Energy Resources: Efficiency and Market Power," Manufacturing & Service Operations Management, INFORMS, vol. 26(3), pages 834-852, May.
    9. Alessio Trivella & Danial Mohseni-Taheri & Selvaprabu Nadarajah, 2023. "Meeting Corporate Renewable Power Targets," Management Science, INFORMS, vol. 69(1), pages 491-512, January.
    10. Heikki Peura & Derek W. Bunn, 2021. "Renewable Power and Electricity Prices: The Impact of Forward Markets," Management Science, INFORMS, vol. 67(8), pages 4772-4788, August.
    11. Luyi Gui & Tinglong Dai, 2026. "Power Couple? AI Growth and Renewable Energy Investment," Papers 2603.26678, arXiv.org.
    12. Yuan Yuan & Feng Cai & Lingling Yang, 2020. "Renewable Energy Investment under Carbon Emission Regulations," Sustainability, MDPI, vol. 12(17), pages 1-15, August.
    13. Nur Sunar & Jayashankar M. Swaminathan, 2021. "Net-Metered Distributed Renewable Energy: A Peril for Utilities?," Management Science, INFORMS, vol. 67(11), pages 6716-6733, November.
    14. Xiaoshan Peng & Owen Q. Wu & Gilvan C. Souza, 2024. "Renewable, Flexible, and Storage Capacities: Friends or Foes?," Manufacturing & Service Operations Management, INFORMS, vol. 26(5), pages 1730-1749, September.
    15. Nur Sunar & Jayashankar M. Swaminathan, 2022. "Socially relevant and inclusive operations management," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4379-4392, December.
    16. Alexandar Angelus, 2021. "Distributed Renewable Power Generation and Implications for Capacity Investment and Electricity Prices," Production and Operations Management, Production and Operations Management Society, vol. 30(12), pages 4614-4634, December.
    17. Simshauser, Paul, 2026. "Are gas turbines ‘bankable’ in transitioning energy-only markets?," Energy Economics, Elsevier, vol. 158(C).
    18. Keppler, Jan Horst & Quemin, Simon & Saguan, Marcelo, 2022. "Why the sustainable provision of low-carbon electricity needs hybrid markets," Energy Policy, Elsevier, vol. 171(C).
    19. Simshauser, Paul, 2024. "On static vs. dynamic line ratings in renewable energy zones," Energy Economics, Elsevier, vol. 129(C).
    20. Jin Yang & Guangxin Jiang & Yinan Wang & Ying Chen, 2025. "An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development," INFORMS Journal on Computing, INFORMS, vol. 37(2), pages 480-501, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

    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:sae:enejou:v:47:y:2026:i:1:p:165-192. 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: SAGE Publications (email available below). General contact details of provider: .

    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.