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A cooperative transactive multi-carrier energy control mechanism with P2P energy + reserve trading using Nash bargaining game theory under renewables uncertainty

Author

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  • Alizadeh, Ali
  • Esfahani, Moein
  • Dinar, Farid
  • Kamwa, Innocent
  • Moeini, Ali
  • Mohseni-Bonab, Seyed Masoud
  • Busvelle, Eric

Abstract

Transactive Energy Control (TEC) as a market-based control is a critical notion for scheduling Multi-Carrier Energy Systems (MCESs) in local networks and forming an Energy Hub (EH). Nevertheless, implementing TEC for scheduling and controlling MCESs is extremely difficult due to the lack of a cooperative TEC model that accounts for network constraints and the uncertainty of Renewable Energy Sources (RESs). This paper defines and formulates Prosumer-Based Multi-Carrier Energy Systems (PB-MCESs), which include electricity, heat, cooling, and gas hubs to enable internal coordination of resources and flexibility extraction for PB-MCESs. Subsequently, Nash Bargaining Game Theory is employed to construct a cooperative TEC that prioritizes P2P energy trade. In addition to P2P energy trading, PB-MCESs can trade their reserve in a P2P fashion to mitigate their uncertainty. PB-MCESs estimate the level of uncertainty using stochastic programming and allot a reserve capacity based on this estimation in order to manage their uncertainty via P2P reserve trading and internal reserves. PB-MCES can also control their risk by altering their risk-taking factor in accordance with the Conditional Value-at-Risk (CVAR) index. Implementations have demonstrated that the proposed cooperative TEC decreases total costs by 17.14% and that the proposed P2P reserve trading reduces total costs by 16.32%.

Suggested Citation

  • Alizadeh, Ali & Esfahani, Moein & Dinar, Farid & Kamwa, Innocent & Moeini, Ali & Mohseni-Bonab, Seyed Masoud & Busvelle, Eric, 2024. "A cooperative transactive multi-carrier energy control mechanism with P2P energy + reserve trading using Nash bargaining game theory under renewables uncertainty," Applied Energy, Elsevier, vol. 353(PB).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pb:s030626192301526x
    DOI: 10.1016/j.apenergy.2023.122162
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    14. Zhai, Chao & Cao, Zhixiang & Wang, Yi & Abdou-Tankari, Mahamadou & Yu, Jian & Lei, Zhen, 2025. "A reverse incentive-based demand response strategy for shared energy storage in industrial microgrids: Optimization, scheduling, and investment analysis," Energy, Elsevier, vol. 330(C).
    15. Barone, G. & Buonomano, A. & Cipolla, G. & Forzano, C. & Giuzio, G.F. & Russo, G., 2024. "Designing aggregation criteria for end-users integration in energy communities: Energy and economic optimisation based on hybrid neural networks models," Applied Energy, Elsevier, vol. 371(C).
    16. Chao Zheng & Wei Huang & Suwei Zhai & Guobiao Lin & Xuehao He & Guanzheng Fang & Shi Su & Di Wang & Qian Ai, 2025. "Collaborative Operation Strategy of Virtual Power Plant Clusters and Distribution Networks Based on Cooperative Game Theory in the Electric–Carbon Coupling Market," Energies, MDPI, vol. 18(16), pages 1-25, August.
    17. Wei, Cunhao & Chen, Zhong & Wang, Yi & Zhang, Ziqi, 2025. "Multi-agent cooperative operation method incorporating electric vehicle operator considering user service selection," Energy, Elsevier, vol. 314(C).
    18. Tang, Yingzhao & Ding, Shixing & Lu, Zhigang & Lu, Shuai & Zhang, Jiangyong & Cai, Yao & Guo, Xiaoqiang, 2026. "Multi-objective hybrid game-theoretic framework with distributionally robust chance constraints for multi-energy microgrid energy management," Applied Energy, Elsevier, vol. 404(C).
    19. Tang, Bao-Jun & Cao, Xi-Lin & Li, Ru & Xiang, Zhi-Bo & Zhang, Sen, 2024. "Economic and low-carbon planning for interconnected integrated energy systems considering emerging technologies and future development trends," Energy, Elsevier, vol. 302(C).
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    21. Wu, Biao & Zhang, Shaohua & Yuan, Chenxin & Wang, Xian & Wang, Fei & Zhang, Shengqi, 2024. "Cooperative energy and reserve trading strategies for multiple integrated energy systems based on asymmetric nash bargaining theory," Energy, Elsevier, vol. 313(C).

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