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Two-stage mechanism design for energy trading of strategic agents in energy communities

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  • Khorasany, Mohsen
  • Razzaghi, Reza
  • Shokri Gazafroudi, Amin

Abstract

This paper proposes a mechanism design for energy trading in energy communities. Each community member is modeled as a strategic agent making strategic actions in interaction with other agents. The proposed mechanism includes two stages, in which in the first stage agents iteratively bid in a day-ahead market, and schedule their energy profiles for the whole operation horizon. Then, in the second stage, agents participate in a one-shot auction for energy trading in each time slot. The two-stage design allows agents to reduce their energy costs by having access to better prices in ahead markets, and also, by granting agents the ability to adjust their bids near real-time, based on their updated demand/generation profile. It is shown that, under mild assumptions on bidding of agents in stage two, the proposed mechanism is Bayes–Nash incentive compatible. Moreover, it is proven that the mechanism is ex-post budget balanced, and individually rational. Case studies demonstrate that the proposed mechanism can reduce the energy costs of the community and helps to reduce the reliance of the community on upstream networks.

Suggested Citation

  • Khorasany, Mohsen & Razzaghi, Reza & Shokri Gazafroudi, Amin, 2021. "Two-stage mechanism design for energy trading of strategic agents in energy communities," Applied Energy, Elsevier, vol. 295(C).
    • Handle: RePEc:eee:appene:v:295:y:2021:i:c:s0306261921004967
    DOI: 10.1016/j.apenergy.2021.117036
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    References listed on IDEAS

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    Cited by:

    1. Zade, Michel & Lumpp, Sebastian Dirk & Tzscheutschler, Peter & Wagner, Ulrich, 2022. "Satisfying user preferences in community-based local energy markets — Auction-based clearing approaches," Applied Energy, Elsevier, vol. 306(PA).
    2. Khorasany, Mohsen & Shokri Gazafroudi, Amin & Razzaghi, Reza & Morstyn, Thomas & Shafie-khah, Miadreza, 2022. "A framework for participation of prosumers in peer-to-peer energy trading and flexibility markets," Applied Energy, Elsevier, vol. 314(C).
    3. Fioriti, Davide & Frangioni, Antonio & Poli, Davide, 2021. "Optimal sizing of energy communities with fair revenue sharing and exit clauses: Value, role and business model of aggregators and users," Applied Energy, Elsevier, vol. 299(C).
    4. Mohammad Hossein Nejati Amiri & Mehdi Mehdinejad & Amin Mohammadpour Shotorbani & Heidarali Shayanfar, 2023. "Heuristic Retailer’s Day-Ahead Pricing Based on Online-Learning of Prosumer’s Optimal Energy Management Model," Energies, MDPI, vol. 16(3), pages 1-21, January.
    5. Gazafroudi, Amin Shokri & Khorasany, Mohsen & Razzaghi, Reza & Laaksonen, Hannu & Shafie-khah, Miadreza, 2021. "Hierarchical approach for coordinating energy and flexibility trading in local energy markets," Applied Energy, Elsevier, vol. 302(C).
    6. Yu Sun & Zhiqiang Ma & Xiaomeng Chi & Jiaqi Duan & Mingxing Li & Asad Ullah Khan, 2024. "Decoding the Developmental Trajectory of Energy Trading in Power Markets through Bibliometric and Visual Analytics," Energies, MDPI, vol. 17(15), pages 1-23, July.
    7. Zabihinia Gerdroodbari, Yasin & Khorasany, Mohsen & Razzaghi, Reza & Heidari, Rahmat, 2024. "Management of prosumers using dynamic export limits and shared Community Energy Storage," Applied Energy, Elsevier, vol. 355(C).
    8. Simoiu, Mircea Stefan & Fagarasan, Ioana & Ploix, Stéphane & Calofir, Vasile, 2022. "Modeling the energy community members’ willingness to change their behaviour with multi-agent systems: A stochastic approach," Renewable Energy, Elsevier, vol. 194(C), pages 1233-1246.
    9. Alaa Al Zetawi & Marcos Tostado-Véliz & Hany M. Hasanien & Francisco Jurado, 2024. "A Robust-Based Home Energy Management Model for Optimal Participation of Prosumers in Competitive P2P Platforms," Energies, MDPI, vol. 17(22), pages 1-22, November.
    10. Zabihinia Gerdroodbari, Yasin & Khorasany, Mohsen & Razzaghi, Reza, 2022. "Dynamic PQ Operating Envelopes for prosumers in distribution networks," Applied Energy, Elsevier, vol. 325(C).
    11. Xie, Xuehua & Qian, Tong & Li, Weiwei & Tang, Wenhu & Xu, Zhao, 2024. "An individualized adaptive distributed approach for fast energy-carbon coordination in transactive multi-community integrated energy systems considering power transformer loading capacity," Applied Energy, Elsevier, vol. 375(C).
    12. Wanessa Guedes & Lucas Deotti & Bruno Dias & Tiago Soares & Leonardo Willer de Oliveira, 2022. "Community Energy Markets with Battery Energy Storage Systems: A General Modeling with Applications," Energies, MDPI, vol. 15(20), pages 1-22, October.

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