IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v383y2025ics0306261925000133.html
   My bibliography  Save this article

Peer-to-peer energy trading of solar and energy storage: A networked multiagent reinforcement learning approach

Author

Listed:
  • Feng, Chen
  • Liu, Andrew L.

Abstract

Utilizing distributed renewable energy resources, particularly solar and energy storage, in local distribution networks via peer-to-peer (P2P) energy trading has long been touted as a solution to improve energy systems’ resilience and sustainability. Consumers and prosumers (that is, those with solar PV and/or energy storage), however, do not have the expertise to engage in repeated P2P trading, and the zero-marginal costs of renewables present challenges in determining fair market prices. To address these issues, we propose multi-agent reinforcement learning (MARL) frameworks to help automate consumers’ bidding and management of their solar PV and energy storage resources, under a specific P2P clearing mechanism that utilizes the so-called supply–demand ratio. In addition, we show how the MARL frameworks can integrate physical network constraints, ensuring the physical feasibility of P2P energy trading and providing a possible pathway for practical deployment.

Suggested Citation

  • Feng, Chen & Liu, Andrew L., 2025. "Peer-to-peer energy trading of solar and energy storage: A networked multiagent reinforcement learning approach," Applied Energy, Elsevier, vol. 383(C).
    • Handle: RePEc:eee:appene:v:383:y:2025:i:c:s0306261925000133
    DOI: 10.1016/j.apenergy.2025.125283
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925000133
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.125283?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. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    2. Tarashandeh, Nader & Karimi, Ali, 2024. "Peer-to-peer energy trading under distribution network constraints with preserving independent nature of agents," Applied Energy, Elsevier, vol. 355(C).
    3. Guannan Qu & Adam Wierman & Na Li, 2022. "Scalable Reinforcement Learning for Multiagent Networked Systems," Operations Research, INFORMS, vol. 70(6), pages 3601-3628, November.
    4. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    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. Félix González & Paul Arévalo & Luis Ramirez, 2025. "Game Theory and Robust Predictive Control for Peer-to-Peer Energy Management: A Pathway to a Low-Carbon Economy," Sustainability, MDPI, vol. 17(5), pages 1-23, February.
    2. Zheyuan Sun & Sara Tavakoli & Kaveh Khalilpour & Alexey Voinov & Jonathan Paul Marshall, 2024. "Barriers to Peer-to-Peer Energy Trading Networks: A Multi-Dimensional PESTLE Analysis," Sustainability, MDPI, vol. 16(4), pages 1-23, February.
    3. Lopez, Hector K. & Zilouchian, Ali, 2023. "Peer-to-peer energy trading for photo-voltaic prosumers," Energy, Elsevier, vol. 263(PA).
    4. Filipe Bandeiras & Álvaro Gomes & Mário Gomes & Paulo Coelho, 2023. "Exploring Energy Trading Markets in Smart Grid and Microgrid Systems and Their Implications for Sustainability in Smart Cities," Energies, MDPI, vol. 16(2), pages 1-41, January.
    5. Zheng, Boshen & Wei, Wei & Chen, Yue & Wu, Qiuwei & Mei, Shengwei, 2022. "A peer-to-peer energy trading market embedded with residential shared energy storage units," Applied Energy, Elsevier, vol. 308(C).
    6. Meritxell Domènech Monfort & César De Jesús & Natapon Wanapinit & Niklas Hartmann, 2022. "A Review of Peer-to-Peer Energy Trading with Standard Terminology Proposal and a Techno-Economic Characterisation Matrix," Energies, MDPI, vol. 15(23), pages 1-29, November.
    7. Arnob Das & Susmita Datta Peu & Md. Abdul Mannan Akanda & Abu Reza Md. Towfiqul Islam, 2023. "RETRACTED: Peer-to-Peer Energy Trading Pricing Mechanisms: Towards a Comprehensive Analysis of Energy and Network Service Pricing (NSP) Mechanisms to Get Sustainable Enviro-Economical Energy Sector," Energies, MDPI, vol. 16(5), pages 1-27, February.
    8. Tsaousoglou, Georgios & Ellinas, Petros & Varvarigos, Emmanouel, 2023. "Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control," Applied Energy, Elsevier, vol. 343(C).
    9. Zeng, Yu & Wei, Xuan & Yao, Yuan & Xu, Yinliang & Sun, Hongbin & Kin Victor Chan, Wai & Feng, Wei, 2023. "Determining the pricing and deployment strategy for virtual power plants of peer-to-peer prosumers: A game-theoretic approach," Applied Energy, Elsevier, vol. 345(C).
    10. Huang, Chung-Ting & Scott, Ian J., 2024. "Peer-to-peer multi-period energy market with flexible scheduling on a scalable and cost-effective blockchain," Applied Energy, Elsevier, vol. 367(C).
    11. Cheng, Xiaoyuan & Yao, Ruiqiu & Postnikov, Andrey & Hu, Yukun & Varga, Liz, 2024. "Decentralized intelligent multi-party competitive aggregation framework for electricity prosumers," Applied Energy, Elsevier, vol. 373(C).
    12. Hosseini Dolatabadi, Sayed Hamid & Bhuiyan, Tanveer Hossain & Chen, Yang & Morales, Jose Luis, 2024. "A stochastic game-theoretic optimization approach for managing local electricity markets with electric vehicles and renewable sources," Applied Energy, Elsevier, vol. 368(C).
    13. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    14. Liu, Yun & Gao, Yunqiang & Borghetti, Alberto & Li, Yuanzheng & Gooi, Hoay Beng & Sun, Chao & Wu, Ting & Zhu, Jizhong, 2024. "A decentralized approach for time-of-use network utilization pricing in peer-to-peer energy markets," Applied Energy, Elsevier, vol. 361(C).
    15. Wicak Ananduta & Sergio Grammatico, 2022. "Equilibrium Seeking and Optimal Selection Algorithms in Peer-to-Peer Energy Markets," Games, MDPI, vol. 13(5), pages 1-13, October.
    16. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    17. Luis Gomes & Hugo Morais & Calvin Gonçalves & Eduardo Gomes & Lucas Pereira & Zita Vale, 2022. "Impact of Forecasting Models Errors in a Peer-to-Peer Energy Sharing Market," Energies, MDPI, vol. 15(10), pages 1-18, May.
    18. Tariq, Abdul Haseeb & Amin, Uzma, 2025. "Peer-to-peer multi-energy trading in a decentralized network: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 208(C).
    19. Lepistö, Juhani & Forcan, Jovana & Forcan, Miodrag, 2024. "Exploring optimal market operations and grid effects in an office building energy community: A case study," Renewable Energy, Elsevier, vol. 231(C).
    20. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

    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:383:y:2025:i:c:s0306261925000133. 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.