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Benefit allocation for combined heat and power dispatch considering mutual trust

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  • Zhao, Leilei
  • Xue, Yixun
  • Sun, Hongbin
  • Du, Yuan
  • Chang, Xinyue
  • Su, Jia
  • Li, Zening

Abstract

Combined heat and power dispatch (CHPD) has attracted wide attention recently, which exploits the potential flexibility in the district heating system (DHS) and provides an economic-effective solution for better wind accommodation. However, DHS operators bear extra operation cost in CHPD, which is proved theoretically in this paper, so that they have insufficient incentive to coordinate with electrical power system. To cope with this issue, a cost allocation strategy based on the Aumann-Shapley value method is proposed, which can rationally allocate the benefit among multiple agents. And a new solution scheme with the Gauss-Legendre quadrature formula is developed to enhance computation efficiency. Also, considering the potential malicious behavior of dishonest agents in the process of allocation, the blockchain framework with Proof of Solution consensus mechanism is introduced to ensure mutual trust among multiple agents. Numerical simulations based on different cases demonstrate the effectiveness of the proposed method of benefit allocation among multiple agents. In addition, the validity of the proposed blockchain framework in preventing malicious behavior when CHPD is verified.

Suggested Citation

  • Zhao, Leilei & Xue, Yixun & Sun, Hongbin & Du, Yuan & Chang, Xinyue & Su, Jia & Li, Zening, 2023. "Benefit allocation for combined heat and power dispatch considering mutual trust," Applied Energy, Elsevier, vol. 345(C).
    • Handle: RePEc:eee:appene:v:345:y:2023:i:c:s0306261923006438
    DOI: 10.1016/j.apenergy.2023.121279
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    as
    1. Alizadeh Bidgoli, Mohsen & Ahmadian, Ali, 2022. "Multi-stage optimal scheduling of multi-microgrids using deep-learning artificial neural network and cooperative game approach," Energy, Elsevier, vol. 239(PB).
    2. Wang, Bohong & Guo, Qinglai & Yu, Yang, 2022. "Mechanism design for data sharing: An electricity retail perspective," Applied Energy, Elsevier, vol. 314(C).
    3. Voswinkel, Simon & Höckner, Jonas & Khalid, Abuzar & Weber, Christoph, 2022. "Sharing congestion management costs among system operators using the Shapley value," Applied Energy, Elsevier, vol. 317(C).
    4. Fang, Fang & Yu, Songyuan & Liu, Mingxi, 2020. "An improved Shapley value-based profit allocation method for CHP-VPP," Energy, Elsevier, vol. 213(C).
    5. Abbasi, Mohammad Hossein & Taki, Mehrdad & Rajabi, Amin & Li, Li & Zhang, Jiangfeng, 2019. "Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach," Applied Energy, Elsevier, vol. 239(C), pages 1294-1307.
    6. Yan, Mingyu & Gan, Wei & Zhou, Yue & Wen, Jianfeng & Yao, Wei, 2022. "Projection method for blockchain-enabled non-iterative decentralized management in integrated natural gas-electric systems and its application in digital twin modelling," Applied Energy, Elsevier, vol. 311(C).
    7. Faria, Victor. A.D. & de Queiroz, Anderson Rodrigo & Lima, Luana M.M. & Lima, José W.M., 2018. "Cooperative game theory and last addition method in the allocation of firm energy rights," Applied Energy, Elsevier, vol. 226(C), pages 905-915.
    8. Churkin, Andrey & Bialek, Janusz & Pozo, David & Sauma, Enzo & Korgin, Nikolay, 2021. "Review of Cooperative Game Theory applications in power system expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    9. Li, Dongsen & Gao, Ciwei & Chen, Tao & Guo, Xiaoxuan & Han, Shuai, 2021. "Planning strategies of power-to-gas based on cooperative game and symbiosis cooperation," Applied Energy, Elsevier, vol. 288(C).
    10. Kristiansen, Martin & Korpås, Magnus & Svendsen, Harald G., 2018. "A generic framework for power system flexibility analysis using cooperative game theory," Applied Energy, Elsevier, vol. 212(C), pages 223-232.
    11. Wang, Yongli & Liu, Zhen & Cai, Chengcong & Xue, Lu & Ma, Yang & Shen, Hekun & Chen, Xin & Liu, Lin, 2022. "Research on the optimization method of integrated energy system operation with multi-subject game," Energy, Elsevier, vol. 245(C).
    12. 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).
    13. Tafakkori–Bafghi, M. & Loghmani, G.B. & Heydari, M., 2022. "Numerical solution of two-point nonlinear boundary value problems via Legendre–Picard iteration method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 199(C), pages 133-159.
    14. Sijie Chen & Hanning Mi & Jian Ping & Zheng Yan & Zeyu Shen & Xuezhi Liu & Ning Zhang & Qing Xia & Chongqing Kang, 2022. "A blockchain consensus mechanism that uses Proof of Solution to optimize energy dispatch and trading," Nature Energy, Nature, vol. 7(6), pages 495-502, June.
    15. Li, Zhengmao & Wu, Lei & Xu, Yan & Wang, Luhao & Yang, Nan, 2023. "Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids," Applied Energy, Elsevier, vol. 331(C).
    16. Sun, Yang & Wang, Ligang & Xu, Cheng & Van herle, Jan & Maréchal, François & Yang, Yongping, 2020. "Enhancing the operational flexibility of thermal power plants by coupling high-temperature power-to-gas," Applied Energy, Elsevier, vol. 263(C).
    17. Liu, Jicheng & Sun, Jiakang & Yuan, Hanying & Su, Yihan & Feng, Shuxian & Lu, Chaoran, 2022. "Behavior analysis of photovoltaic-storage-use value chain game evolution in blockchain environment," Energy, Elsevier, vol. 260(C).
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    1. Zheng, Weiye & Xu, Siyu & Liu, Jiawei & Zhu, Jizhong & Luo, Qingju, 2023. "Participation of strategic district heating networks in electricity markets: An arbitrage mechanism and its equilibrium analysis," Applied Energy, Elsevier, vol. 350(C).
    2. Zhao, Bingxu & Cao, Xiaodong & Duan, Pengfei, 2024. "Cooperative operation of multiple low-carbon microgrids: An optimization study addressing gaming fraud and multiple uncertainties," Energy, Elsevier, vol. 297(C).

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