IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v368y2024ics0306261924008894.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924008894
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123506?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. 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)

    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. Xu, Xun & Shao, Zhenguo & Chen, Feixiong & Cheng, Guoyang, 2024. "Multi-game optimization operation strategy for integrated energy system considering spatiotemporal correlation of renewable energy," Energy, Elsevier, vol. 303(C).
    2. Ahmadisedigh, Hossein & Gosselin, Louis, 2022. "How can combined heating and cooling networks benefit from thermal energy storage? Minimizing lifetime cost for different scenarios," Energy, Elsevier, vol. 243(C).
    3. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    4. Zhu, Yilin & Xu, Yujie & Chen, Haisheng & Guo, Huan & Zhang, Hualiang & Zhou, Xuezhi & Shen, Haotian, 2023. "Optimal dispatch of a novel integrated energy system combined with multi-output organic Rankine cycle and hybrid energy storage," Applied Energy, Elsevier, vol. 343(C).
    5. Xie, Shiwei & Hu, Zhijian & Wang, Jueying & Chen, Yuwei, 2020. "The optimal planning of smart multi-energy systems incorporating transportation, natural gas and active distribution networks," Applied Energy, Elsevier, vol. 269(C).
    6. Yu Huang & Weiting Zhang & Kai Yang & Weizhen Hou & Yiran Huang, 2019. "An Optimal Scheduling Method for Multi-Energy Hub Systems Using Game Theory," Energies, MDPI, vol. 12(12), pages 1-20, June.
    7. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    8. Xie, Shiwei & Zheng, Jieyun & Hu, Zhijian & Wang, Jueying & Chen, Yuwei, 2020. "Urban multi-energy network optimization: An enhanced model using a two-stage bound-tightening approach," Applied Energy, Elsevier, vol. 277(C).
    9. Liu, Dewen & Luo, Zhao & Qin, Jinghui & Wang, Hua & Wang, Gang & Li, Zhao & Zhao, Weijie & Shen, Xin, 2023. "Low-carbon dispatch of multi-district integrated energy systems considering carbon emission trading and green certificate trading," Renewable Energy, Elsevier, vol. 218(C).
    10. Cai, Pengcheng & Mi, Yang & Ma, Siyuan & Li, Hongzhong & Li, Dongdong & Wang, Peng, 2023. "Hierarchical game for integrated energy system and electricity-hydrogen hybrid charging station under distributionally robust optimization," Energy, Elsevier, vol. 283(C).
    11. Wu, Min & Xu, Jiazhu & Zeng, Linjun & Li, Chang & Liu, Yuxing & Yi, Yuqin & Wen, Ming & Jiang, Zhuohan, 2022. "Two-stage robust optimization model for park integrated energy system based on dynamic programming," Applied Energy, Elsevier, vol. 308(C).
    12. Qin, Chun & Zhao, Jun & Chen, Long & Liu, Ying & Wang, Wei, 2022. "An adaptive piecewise linearized weighted directed graph for the modeling and operational optimization of integrated energy systems," Energy, Elsevier, vol. 244(PA).
    13. Meng, Anbo & Wu, Zhenbo & Zhang, Zhan & Xu, Xuancong & Tang, Yanshu & Xie, Zhifeng & Xian, Zikang & Zhang, Haitao & Luo, Jianqiang & Wang, Yu & Yan, Baiping & Yin, Hao, 2024. "Optimal scheduling of integrated energy system using decoupled distributed CSO with opposition-based learning and neighborhood re-dispatch strategy," Renewable Energy, Elsevier, vol. 224(C).
    14. 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).
    15. Duan, Pengfei & Zhao, Bingxu & Zhang, Xinghui & Fen, Mengdan, 2023. "A day-ahead optimal operation strategy for integrated energy systems in multi-public buildings based on cooperative game," Energy, Elsevier, vol. 275(C).
    16. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad & Hajizadeh, Amin & Mohammadi-ivatloo, Behnam, 2022. "A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    17. 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).
    18. Ma, Tengfei & Wu, Junyong & Hao, Liangliang & Lee, Wei-Jen & Yan, Huaguang & Li, Dezhi, 2018. "The optimal structure planning and energy management strategies of smart multi energy systems," Energy, Elsevier, vol. 160(C), pages 122-141.
    19. Mansouri, Seyed Amir & Ahmarinejad, Amir & Javadi, Mohammad Sadegh & Catalão, João P.S., 2020. "Two-stage stochastic framework for energy hubs planning considering demand response programs," Energy, Elsevier, vol. 206(C).
    20. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).

    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:368:y:2024:i:c:s0306261924008894. 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.