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Bilateral planning and operation for integrated energy service provider and prosumers - A Nash bargaining-based method

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  • Jiang, Qian
  • Jia, Hongjie
  • Mu, Yunfei
  • Yu, Xiaodan
  • Wang, Zibo

Abstract

Integrated community energy systems (ICESs) facilitate stakeholders to collaboratively create profit by planning and operating energy devices, including generation, conversion, and storage systems. However, the coupling and complementarity of multiple energy carriers, along with the comprehensive interaction among independent stakeholders, pose significant challenges in ICES planning and operating. These challenges necessitate balancing overall economic efficiency with individual stakeholder interests. This study investigates the economic interaction between the integrated energy service provider (IESP) and the photovoltaic energy prosumers (EPs) in ICES from a cooperative perspective, focusing on both planning and operating stage. A bilateral planning and operation method for the IESP and the EPs based on Nash bargaining theory is proposed in this paper. The proposed method establishes a cooperative and mutually beneficial relationship between the IESP and EPs, instead of a hierarchical paradigm. This study also presents an analysis of the relationship between the Nash bargaining problem and the social welfare maximization problem, demonstrating that solving the Nash bargaining problem can lead to a social welfare optimum. Additionally, an accelerated privacy-preserving distributed algorithm, in comparison to the central approach, is designed to solve the Nash bargaining problem. Numerical studies based on realistic data reveal that the Nash bargaining-based planning and operation method provides more benefits for both the IESP and EPs, as compared to the non-cooperation game method.

Suggested Citation

  • Jiang, Qian & Jia, Hongjie & Mu, Yunfei & Yu, Xiaodan & Wang, Zibo, 2024. "Bilateral planning and operation for integrated energy service provider and prosumers - A Nash bargaining-based method," Applied Energy, Elsevier, vol. 368(C).
    • Handle: RePEc:eee:appene:v:368:y:2024:i:c:s0306261924008894
    DOI: 10.1016/j.apenergy.2024.123506
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    References listed on IDEAS

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    1. Yan, Haoran & Hou, Hongjuan & Deng, Min & Si, Lengge & Wang, Xi & Hu, Eric & Zhou, Rhonin, 2024. "Stackelberg game theory based model to guide users’ energy use behavior, with the consideration of flexible resources and consumer psychology, for an integrated energy system," Energy, Elsevier, vol. 288(C).
    2. Jiang, Qian & Mu, Yunfei & Jia, Hongjie & Cao, Yan & Wang, Zibo & Wei, Wei & Hou, Kai & Yu, Xiaodan, 2022. "A Stackelberg Game-based planning approach for integrated community energy system considering multiple participants," Energy, Elsevier, vol. 258(C).
    3. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    4. Jiang, Aihua & Yuan, Huihong & Li, Delong, 2021. "Energy management for a community-level integrated energy system with photovoltaic prosumers based on bargaining theory," Energy, Elsevier, vol. 225(C).
    5. Wang, Yi & Zhang, Ning & Zhuo, Zhenyu & Kang, Chongqing & Kirschen, Daniel, 2018. "Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch," Applied Energy, Elsevier, vol. 210(C), pages 1141-1150.
    6. Chen, Cong & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "Two-stage robust planning-operation co-optimization of energy hub considering precise energy storage economic model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    7. Mu, Yunfei & Chen, Wanqing & Yu, Xiaodan & Jia, Hongjie & Hou, Kai & Wang, Congshan & Meng, Xianjun, 2020. "A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies," Applied Energy, Elsevier, vol. 279(C).
    8. Wang, Yifeng & Jiang, Aihua & Wang, Rui & Tian, Junyang, 2024. "A canonical coalitional game model incorporating motivational psychology analysis for incentivizing stable direct energy trading in smart grid," Energy, Elsevier, vol. 289(C).
    9. Oskouei, Morteza Zare & Mohammadi-Ivatloo, Behnam & Abapour, Mehdi & Shafiee, Mahmood & Anvari-Moghaddam, Amjad, 2021. "Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs," Applied Energy, Elsevier, vol. 283(C).
    10. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    11. Ma, Tengfei & Pei, Wei & Deng, Wei & Xiao, Hao & Yang, Yanhong & Tang, Chenghong, 2022. "A Nash bargaining-based cooperative planning and operation method for wind-hydrogen-heat multi-agent energy system," Energy, Elsevier, vol. 239(PE).
    12. Mu, Chenlu & Ding, Tao & Qu, Ming & Zhou, Quan & Li, Fangxing & Shahidehpour, Mohammad, 2020. "Decentralized optimization operation for the multiple integrated energy systems with energy cascade utilization," Applied Energy, Elsevier, vol. 280(C).
    Full references (including those not matched with items on IDEAS)

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