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A Bilevel robust coordination model for community integrated energy system with access to HFCEVs and EVs

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  • Gu, Bo
  • Li, Fangxing
  • Mao, Chengxiong
  • Wang, Dan
  • Fan, Hua
  • Liu, Bin
  • Li, Wenhao

Abstract

It is of great interest to a price-maker community integrated energy system (CIES) that hydrogen fuel cell electric vehicle (HFCEV) and electric vehicle (EV) clusters participate in the system operation to achieve better flexibility. As such, this paper proposes a bilevel coordination optimization model considering the multiple uncertainties from each entity to minimize the operation cost. The Stackelberg game-based pricing framework is used to formulate the optimal model. The modeling of HFCEVs is based on the distributionally robust chance constrained problem to efficiently address the uncertainties from hydrogen refueling stations (HRSs). EVs are grouped into different classes via a clustering method, and the distributionally robust optimization model is built. Simulation results show that the proposed robust coordination optimization model reduces the operation cost by 0.76 %–2.01 % and improve the robustness under multiple uncertainties from each entity, maintaining about 50 % safety capacity for HRS.

Suggested Citation

  • Gu, Bo & Li, Fangxing & Mao, Chengxiong & Wang, Dan & Fan, Hua & Liu, Bin & Li, Wenhao, 2025. "A Bilevel robust coordination model for community integrated energy system with access to HFCEVs and EVs," Applied Energy, Elsevier, vol. 390(C).
    • Handle: RePEc:eee:appene:v:390:y:2025:i:c:s0306261925005963
    DOI: 10.1016/j.apenergy.2025.125866
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    References listed on IDEAS

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    1. Chen, Lin & Tang, Zhiyuan & He, Shuaijia & Liu, Junyong, 2024. "Feasible operation region estimation of virtual power plant considering heterogeneity and uncertainty of distributed energy resources," Applied Energy, Elsevier, vol. 362(C).
    2. Huang, Xingjun & Lin, Yun & Lim, Ming K. & Zhou, Fuli & Liu, Feng, 2022. "Electric vehicle charging station diffusion: An agent-based evolutionary game model in complex networks," Energy, Elsevier, vol. 257(C).
    3. Pham, An T. & Lovdal, Larson & Zhang, Tianyi & Craig, Michael T., 2022. "A techno-economic analysis of distributed energy resources versus wholesale electricity purchases for fueling decarbonized heavy duty vehicles," Applied Energy, Elsevier, vol. 322(C).
    4. Panah, Payam Ghaebi & Bornapour, Mosayeb & Hemmati, Reza & Guerrero, Josep M., 2021. "Charging station Stochastic Programming for Hydrogen/Battery Electric Buses using Multi-Criteria Crow Search Algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    5. Meng, Weiqi & Song, Dongran & Huang, Liansheng & Chen, Xiaojiao & Yang, Jian & Dong, Mi & Talaat, M. & Elkholy, M.H., 2024. "Distributed energy management of electric vehicle charging stations based on hierarchical pricing mechanism and aggregate feasible regions," Energy, Elsevier, vol. 291(C).
    6. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
    7. Xia, Weiyi & Ren, Zhouyang & Qin, Huiling & Dong, ZhaoYang, 2024. "A coordinated operation method for networked hydrogen-power-transportation system," Energy, Elsevier, vol. 296(C).
    8. Ioana Popescu, 2007. "Robust Mean-Covariance Solutions for Stochastic Optimization," Operations Research, INFORMS, vol. 55(1), pages 98-112, February.
    9. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    10. Ajanovic, A. & Glatt, A. & Haas, R., 2021. "Prospects and impediments for hydrogen fuel cell buses," Energy, Elsevier, vol. 235(C).
    11. Gao, Yizhao & Zhu, Chong & Zhang, Xi & Guo, Bangjun, 2021. "Implementation and evaluation of a practical electrochemical- thermal model of lithium-ion batteries for EV battery management system," Energy, Elsevier, vol. 221(C).
    12. Grani A. Hanasusanto & Vladimir Roitch & Daniel Kuhn & Wolfram Wiesemann, 2017. "Ambiguous Joint Chance Constraints Under Mean and Dispersion Information," Operations Research, INFORMS, vol. 65(3), pages 751-767, June.
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