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Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game

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Listed:
  • Li, Peng
  • Wang, Zixuan
  • Yang, Weihong
  • Liu, Haitao
  • Yin, Yunxing
  • Wang, Jiahao
  • Guo, Tianyu

Abstract

-- With the rapid development of the energy internet, integrated energy system (IES) has become a topic of interest in the field of energy research. In light of energy interconnection system containing multiple communities, this paper proposes a hierarchically partitioned coordinated operation method for distributed integrated energy system (DIES) based on a master-slave game. First, based on the concept of "distributed autonomy and centralized coordination", a hierarchically partitioned structure of urban integrated energy system is given, and a variety of energy equipment are modeled and analysed. Next, in considering the energy and interest interactions among different communities, the urban manager and community operators are taken as the game leader and game followers, respectively, to establish a hierarchically partitioned master-slave game optimization model of DIES based on game theory, and a mixed integer linear programming method is applied to solve the model. Finally, a typical case of urban integrated energy system is taken as an example to verify the optimization model. Simulation results show that the proposed method can effectively promote the balance of energy supply and demand, and reconcile the benefits of leader and followers, while further realizing the economic, flexible and efficient operation of DIES.

Suggested Citation

  • Li, Peng & Wang, Zixuan & Yang, Weihong & Liu, Haitao & Yin, Yunxing & Wang, Jiahao & Guo, Tianyu, 2021. "Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game," Energy, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:energy:v:214:y:2021:i:c:s0360544220321137
    DOI: 10.1016/j.energy.2020.119006
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    References listed on IDEAS

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    Cited by:

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    3. 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).
    4. Zhou, Yuan & Wang, Jiangjiang & Yang, Mingxu & Xu, Hangwei, 2023. "Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology," Applied Energy, Elsevier, vol. 349(C).
    5. Fan, Wei & Tan, Qingbo & Zhang, Amin & Ju, Liwei & Wang, Yuwei & Yin, Zhe & Li, Xudong, 2023. "A Bi-level optimization model of integrated energy system considering wind power uncertainty," Renewable Energy, Elsevier, vol. 202(C), pages 973-991.
    6. Li, Peng & Guo, Tianyu & Abeysekera, Muditha & Wu, Jianzhong & Han, Zhonghe & Wang, Zixuan & Yin, Yunxing & Zhou, Fengquan, 2021. "Intraday multi-objective hierarchical coordinated operation of a multi-energy system," Energy, Elsevier, vol. 228(C).
    7. Ding, Jianyong & Gao, Ciwei & Song, Meng & Yan, Xingyu & Chen, Tao, 2022. "Bi-level optimal scheduling of virtual energy station based on equal exergy replacement mechanism," Applied Energy, Elsevier, vol. 327(C).

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