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Decentralized coordinated operation model of VPP and P2H systems based on stochastic-bargaining game considering multiple uncertainties and carbon cost

Author

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  • Wang, Xuejie
  • zhao, Huiru
  • Lu, Hao
  • Zhang, Yuanyuan
  • Wang, Yuwei
  • Wang, Jingbo

Abstract

In order to achieve low-carbon development, the joint operation of virtual power plants (VPP) and clean power to hydrogen (P2H) is a hot issue. However, the conventional centralized optimization strategy ignores the information asymmetry between VPP and P2H, resulting in disorderly competition and low market efficiency. Based on this, this paper proposes a decentralized coordinated operation method of the VPP-P2H combined system considering the profits of each player. First, the stochastic optimization operation model of VPP and P2H is built involving the multiple uncertainties on both sides of the source and load. Secondly, based on the Nash-Harsanyi bargaining game theory, a multi-agent decentralized coordinated operation model of VPP-P2H is established. The model is further equivalent to the minimization of coordinated operation cost sub-problem and payment bargaining sub-problem. For the privacy of each player, the improved alternating direction multiplier method (ADMM) is used to solve the above two sub-problems. Finally, the effectiveness of the proposed decentralized coordinated operation model and distributed algorithm are verified. The simulation results show that compared with the individual operation mode, through coordinated operation, the operating costs of P2H1, P2H2, and VPP are reduced by 19.59%, 18.18%, and 16.61%, respectively. In addition, the improved-ADMM algorithm also improves the solution efficiency of the system.

Suggested Citation

  • Wang, Xuejie & zhao, Huiru & Lu, Hao & Zhang, Yuanyuan & Wang, Yuwei & Wang, Jingbo, 2022. "Decentralized coordinated operation model of VPP and P2H systems based on stochastic-bargaining game considering multiple uncertainties and carbon cost," Applied Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:appene:v:312:y:2022:i:c:s0306261922002069
    DOI: 10.1016/j.apenergy.2022.118750
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    References listed on IDEAS

    as
    1. Yao, Xing & Zhong, Ping & Zhang, Xian & Zhu, Lei, 2018. "Business model design for the carbon capture utilization and storage (CCUS) project in China," Energy Policy, Elsevier, vol. 121(C), pages 519-533.
    2. Li, Yanfu & Zio, Enrico, 2012. "Uncertainty analysis of the adequacy assessment model of a distributed generation system," Renewable Energy, Elsevier, vol. 41(C), pages 235-244.
    3. Uchman, Wojciech & Skorek-Osikowska, Anna & Jurczyk, Michał & Węcel, Daniel, 2020. "The analysis of dynamic operation of power-to-SNG system with hydrogen generator powered with renewable energy, hydrogen storage and methanation unit," Energy, Elsevier, vol. 213(C).
    4. Wang, Yifei & Wang, Xiuli & Shao, Chengcheng & Gong, Naiwei, 2020. "Distributed energy trading for an integrated energy system and electric vehicle charging stations: A Nash bargaining game approach," Renewable Energy, Elsevier, vol. 155(C), pages 513-530.
    5. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    6. Du, Yan & Wang, Zhiwei & Liu, Guangyi & Chen, Xi & Yuan, Haoyu & Wei, Yanli & Li, Fangxing, 2018. "A cooperative game approach for coordinating multi-microgrid operation within distribution systems," Applied Energy, Elsevier, vol. 222(C), pages 383-395.
    7. Lozano, S. & Moreno, P. & Adenso-Díaz, B. & Algaba, E., 2013. "Cooperative game theory approach to allocating benefits of horizontal cooperation," European Journal of Operational Research, Elsevier, vol. 229(2), pages 444-452.
    8. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    9. Li, Nan & Zhao, Xunwen & Shi, Xunpeng & Pei, Zhenwei & Mu, Hailin & Taghizadeh-Hesary, Farhad, 2021. "Integrated energy systems with CCHP and hydrogen supply: A new outlet for curtailed wind power," Applied Energy, Elsevier, vol. 303(C).
    10. Wang, Lu & Gu, Wei & Wu, Zhi & Qiu, Haifeng & Pan, Guangsheng, 2020. "Non-cooperative game-based multilateral contract transactions in power-heating integrated systems," Applied Energy, Elsevier, vol. 268(C).
    11. Ishaq, H. & Dincer, I., 2021. "Comparative assessment of renewable energy-based hydrogen production methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    12. Klyapovskiy, Sergey & Zheng, Yi & You, Shi & Bindner, Henrik W., 2021. "Optimal operation of the hydrogen-based energy management system with P2X demand response and ammonia plant," Applied Energy, Elsevier, vol. 304(C).
    13. Wu, Xiong & Qi, Shixiong & Wang, Zhao & Duan, Chao & Wang, Xiuli & Li, Furong, 2019. "Optimal scheduling for microgrids with hydrogen fueling stations considering uncertainty using data-driven approach," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    14. Wei, Chun & Shen, Zhuzheng & Xiao, Dongliang & Wang, Licheng & Bai, Xiaoqing & Chen, Haoyong, 2021. "An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining," Applied Energy, Elsevier, vol. 295(C).
    15. Qureshy, Ali M.M.I. & Dincer, Ibrahim, 2020. "Energy and exergy analyses of an integrated renewable energy system for hydrogen production," Energy, Elsevier, vol. 204(C).
    Full references (including those not matched with items on IDEAS)

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    3. Guixing Yang & Haoran Liu & Weiqing Wang & Junru Chen & Shunbo Lei, 2023. "Distributed Optimal Coordination of a Virtual Power Plant with Residential Regenerative Electric Heating Systems," Energies, MDPI, vol. 16(11), pages 1-15, May.
    4. Huiru Zhao & Chao Zhang & Yihang Zhao & Xuejie Wang, 2022. "Low-Carbon Economic Dispatching of Multi-Energy Virtual Power Plant with Carbon Capture Unit Considering Uncertainty and Carbon Market," Energies, MDPI, vol. 15(19), pages 1-25, October.
    5. Xu, Jiazhu & Yi, Yuqin, 2023. "Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach," Energy, Elsevier, vol. 263(PB).
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    7. Zheng, Weiye & Lu, Hao & Zhu, Jizhong, 2023. "Incentivizing cooperative electricity-heat operation: A distributed asymmetric Nash bargaining mechanism," Energy, Elsevier, vol. 280(C).
    8. Wang, Beibei & Xu, Lun & Wang, Jialei, 2023. "A privacy-preserving trading strategy for blockchain-based P2P electricity transactions," Applied Energy, Elsevier, vol. 335(C).

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