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Grid-Oriented Coordination Strategy of Prosumers Using Game-theoretic Peer-to-Peer Trading Framework in Energy Community

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  • Lee, Won-Poong
  • Han, Dongjun
  • Won, Dongjun

Abstract

In this paper, a grid-oriented peer-to-peer (P2P) energy transaction strategy based on game theory that considers participants with diversity in trading and the impact on the system of trading is studied. For this, the optimization problem of prosumers with ESS is defined according to the lifetime cost of the ESS. The proposed energy trading strategy is carried out based on three game theories. Among them, the evolutionary game between buyers, non-cooperative games between sellers, and Stackelberg games between sellers and buyers are considered. When all games are played sequentially and the convergence point is reached, the negotiation is determined and then ends and a contract is made based on trading price and amount. As a novel contribution in the case of the evolutionary game the community manager indirectly provides information on the system so that when evaluating the seller, the effect on the system is applied as a loss change. In addition, when deriving a utility value by payoff, it is set as an increase/decrease ratio compared to the initial value so that the game proceeds regardless of the size of the participants and the defined problem. To verify the effectiveness of the proposed P2P energy trading strategy, a simulation based on MATLAB is performed. It is confirmed that the effect on the grid is applied to the seller's selling price. When the strategy proposed in the P2P energy trading is applied, the increased purchase and selling amount due to the trading increased by 3.41 % and 4.51 %, respectively, he difference between increased puchase and selling amount decreases by about 36 % from 3.181 kW to 2.03 kW, and the loss due to the change in trading amount also decreased by 1.59 %. This means that the grid impact has been reflected in the P2P energy trading, resulting in efficient operation, and it is the reason for grid operators to accept P2P energy trading. In conclusion, the results of the proposed strategy prove that efficiency in energy use is increased by considering the impacts of the power system in P2P energy trading.

Suggested Citation

  • Lee, Won-Poong & Han, Dongjun & Won, Dongjun, 2022. "Grid-Oriented Coordination Strategy of Prosumers Using Game-theoretic Peer-to-Peer Trading Framework in Energy Community," Applied Energy, Elsevier, vol. 326(C).
  • Handle: RePEc:eee:appene:v:326:y:2022:i:c:s0306261922012375
    DOI: 10.1016/j.apenergy.2022.119980
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    References listed on IDEAS

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    1. Javadi, Mohammad Sadegh & Esmaeel Nezhad, Ali & Jordehi, Ahmad Rezaee & Gough, Matthew & Santos, Sérgio F. & Catalão, João P.S., 2022. "Transactive energy framework in multi-carrier energy hubs: A fully decentralized model," Energy, Elsevier, vol. 238(PB).
    2. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.
    3. Wonpoong Lee & Myeongseok Chae & Dongjun Won, 2022. "Optimal Scheduling of Energy Storage System Considering Life-Cycle Degradation Cost Using Reinforcement Learning," Energies, MDPI, vol. 15(8), pages 1-19, April.
    4. Zhou, Yue & Wu, Jianzhong & Long, Chao, 2018. "Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework," Applied Energy, Elsevier, vol. 222(C), pages 993-1022.
    5. Long, Chao & Wu, Jianzhong & Zhou, Yue & Jenkins, Nick, 2018. "Peer-to-peer energy sharing through a two-stage aggregated battery control in a community Microgrid," Applied Energy, Elsevier, vol. 226(C), pages 261-276.
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    Cited by:

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    2. Anna Ostrowska & Tomasz Sikorski & Alessandro Burgio & Michał Jasiński, 2023. "Modern Use of Prosumer Energy Regulation Capabilities for the Provision of Microgrid Flexibility Services," Energies, MDPI, vol. 16(1), pages 1-13, January.
    3. Lefeng Cheng & Xin Wei & Manling Li & Can Tan & Meng Yin & Teng Shen & Tao Zou, 2024. "Integrating Evolutionary Game-Theoretical Methods and Deep Reinforcement Learning for Adaptive Strategy Optimization in User-Side Electricity Markets: A Comprehensive Review," Mathematics, MDPI, vol. 12(20), pages 1-56, October.
    4. Wu, Chun & Chen, Xingying & Hua, Haochen & Yu, Kun & Gan, Lei & Shen, Jun & Ding, Yi, 2024. "Peer-to-peer energy trading optimization for community prosumers considering carbon cap-and-trade," Applied Energy, Elsevier, vol. 358(C).
    5. Xin, Baogui & Zhang, Mengwei, 2023. "Evolutionary game on international energy trade under the Russia-Ukraine conflict," Energy Economics, Elsevier, vol. 125(C).
    6. Barone, G. & Buonomano, A. & Forzano, C. & Palombo, A. & Russo, G., 2023. "The role of energy communities in electricity grid balancing: A flexible tool for smart grid power distribution optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    7. Liao, Wei & Xiao, Fu & Li, Yanxue & Peng, Jinqing, 2024. "Comparative study on electricity transactions between multi-microgrid: A hybrid game theory-based peer-to-peer trading in heterogeneous building communities considering electric vehicles," Applied Energy, Elsevier, vol. 367(C).
    8. Bożena Gajdzik & Magdalena Jaciow & Radosław Wolniak & Robert Wolny & Wieslaw Wes Grebski, 2023. "Energy Behaviors of Prosumers in Example of Polish Households," Energies, MDPI, vol. 16(7), pages 1-26, March.
    9. Li, Ke & Ye, Ning & Li, Shuzhen & Wang, Haiyang & Zhang, Chenghui, 2023. "Distributed collaborative operation strategies in multi-agent integrated energy system considering integrated demand response based on game theory," Energy, Elsevier, vol. 273(C).
    10. Meng, Yuan & Qiu, Jing & Zhang, Cuo & Lei, Gang & Zhu, Jianguo, 2024. "A Holistic P2P market for active and reactive energy trading in VPPs considering both financial benefits and network constraints," Applied Energy, Elsevier, vol. 356(C).

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