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Hierarchical game for integrated energy system and electricity-hydrogen hybrid charging station under distributionally robust optimization

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Listed:
  • Cai, Pengcheng
  • Mi, Yang
  • Ma, Siyuan
  • Li, Hongzhong
  • Li, Dongdong
  • Wang, Peng

Abstract

To facilitate energy coupling and distributed coordinate the economic improvement needs of multi-stakeholders, a bi-level strategic operation framework is proposed for integrated energy system (IES) with electricity-hydrogen hybrid charging station (HCS) via utilizing the distributionally robust optimization (DRO) approach together with hierarchical game. Firstly, a Stackelberg game dynamic pricing strategy with the IES plays the leader at the upper level while the HCS is regarded as the follower at the lower level is established, in which electricity price and power are the only interactive information. Secondly, a comprehensive norm consisting of 1-norm and ∞-norm is elaborately constructed as the uncertainty probability information ambiguity set to capture the uncertainty of intractable electric vehicles' type characteristics in the HCS. Besides, a solving technique of the bisection-based distributed algorithm combined with the column-and-constraint generation algorithm is presented to overcome the convergence difficulty in the two-stage mathematical programming model with lower-level nonconvex problems. Finally, numerical simulation results are conducted confirming the priority of the employed model and method in balancing conflicts of interest, compromising economy and robustness, as well as the computational efficiency of the algorithm.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223018650
    DOI: 10.1016/j.energy.2023.128471
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    1. Uris, María & Linares, José Ignacio & Arenas, Eva, 2017. "Feasibility assessment of an Organic Rankine Cycle (ORC) cogeneration plant (CHP/CCHP) fueled by biomass for a district network in mainland Spain," Energy, Elsevier, vol. 133(C), pages 969-985.
    2. Wang, Yaxian & Zhao, Zhenli & Baležentis, Tomas, 2023. "Benefit distribution in shared private charging pile projects based on modified Shapley value," Energy, Elsevier, vol. 263(PB).
    3. Li, Yang & Han, Meng & Shahidehpour, Mohammad & Li, Jiazheng & Long, Chao, 2023. "Data-driven distributionally robust scheduling of community integrated energy systems with uncertain renewable generations considering integrated demand response," Applied Energy, Elsevier, vol. 335(C).
    4. 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).
    5. Tan, Jinjing & Li, Yang & Zhang, Xiaoping & Pan, Weiqi & Ruan, Wenjun, 2023. "Operation of a commercial district integrated energy system considering dynamic integrated demand response: A Stackelberg game approach," Energy, Elsevier, vol. 274(C).
    6. Zhang, Yachao & Liu, Yan & Shu, Shengwen & Zheng, Feng & Huang, Zhanghao, 2021. "A data-driven distributionally robust optimization model for multi-energy coupled system considering the temporal-spatial correlation and distribution uncertainty of renewable energy sources," Energy, Elsevier, vol. 216(C).
    7. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    8. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
    9. Gao, Hongjun & Cai, Wenhui & He, Shuaijia & Liu, Chang & Liu, Junyong, 2023. "Stackelberg game based energy sharing for zero-carbon community considering reward and punishment of carbon emission," Energy, Elsevier, vol. 277(C).
    10. Wang, Liying & Lin, Jialin & Dong, Houqi & Wang, Yuqing & Zeng, Ming, 2023. "Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system," Energy, Elsevier, vol. 270(C).
    11. Fang, Xiaolun & Wang, Yubin & Dong, Wei & Yang, Qiang & Sun, Siyang, 2023. "Optimal energy management of multiple electricity-hydrogen integrated charging stations," Energy, Elsevier, vol. 262(PB).
    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. Chen, Yujia & Pei, Wei & Ma, Tengfei & Xiao, Hao, 2023. "Asymmetric Nash bargaining model for peer-to-peer energy transactions combined with shared energy storage," Energy, Elsevier, vol. 278(PB).
    14. Walter Gil-González & Oscar Danilo Montoya & Arul Rajagopalan & Luis Fernando Grisales-Noreña & Jesus C. Hernández, 2020. "Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm," Energies, MDPI, vol. 13(18), pages 1-21, September.
    15. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Nash bargaining based collaborative energy management for regional integrated energy systems in uncertain electricity markets," Energy, Elsevier, vol. 269(C).
    16. 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).
    17. Mei, Fei & Zhang, Jiatang & Lu, Jixiang & Lu, Jinjun & Jiang, Yuhan & Gu, Jiaqi & Yu, Kun & Gan, Lei, 2021. "Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations," Energy, Elsevier, vol. 219(C).
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