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Multi-Objective Robust Optimization of Integrated Energy System with Hydrogen Energy Storage

Author

Listed:
  • Yuyang Zhao

    (School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    Hebei Engineering Laboratory of Wind Power and Photovoltaic Coupling Hydrogen Production and Comprehensive Utilization, Shijiazhuang 050018, China)

  • Yifan Wei

    (School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China)

  • Shuaiqi Zhang

    (School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China)

  • Yingjun Guo

    (School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    Hebei Engineering Laboratory of Wind Power and Photovoltaic Coupling Hydrogen Production and Comprehensive Utilization, Shijiazhuang 050018, China)

  • Hexu Sun

    (School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    Hebei Engineering Laboratory of Wind Power and Photovoltaic Coupling Hydrogen Production and Comprehensive Utilization, Shijiazhuang 050018, China)

Abstract

A novel multi-objective robust optimization model of an integrated energy system with hydrogen storage (HIES) considering source–load uncertainty is proposed to promote the low-carbon economy operation of the integrated energy system of a park. Firstly, the lowest total system cost and carbon emissions are selected as the multi-objective optimization functions. The Pareto front solution set of the objective function is applied by compromise planning, and the optimal solution among them is obtained by the maximum–minimum fuzzy method. Furthermore, the robust optimization (RO) approach is introduced to cope with the source–load uncertainty effectively. Finally, it is demonstrated that the illustrated HIES can significantly reduce the total system cost, carbon emissions, and abandoned wind and solar power. Meanwhile, the effectiveness of the proposed model and solution method is verified by analyzing the influence of multi-objective solutions and a robust coefficient on the Chongli Demonstration Project in Hebei Province.

Suggested Citation

  • Yuyang Zhao & Yifan Wei & Shuaiqi Zhang & Yingjun Guo & Hexu Sun, 2024. "Multi-Objective Robust Optimization of Integrated Energy System with Hydrogen Energy Storage," Energies, MDPI, vol. 17(5), pages 1-20, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:5:p:1132-:d:1346963
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    References listed on IDEAS

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    Cited by:

    1. Wang, Huiyuan & Jia, Chaoyu & Jia, Hongjie & Mu, Yunfei & Xu, Xiandong & Yu, Xiaodan, 2025. "A planning method for park-level integrated energy system based on system integration theory," Applied Energy, Elsevier, vol. 388(C).
    2. Hossein Faramarzi & Navid Ghaffarzadeh & Farhad Shahnia, 2025. "Intelligent Management of Integrated Energy Systems with a Stochastic Multi-Objective Approach with Emphasis on Demand Response, Energy Storage Devices, and Power-to-Gas," Sustainability, MDPI, vol. 17(7), pages 1-28, March.
    3. Li, Ru & Lu, Yaxi & Guo, Yan & Zhang, Chen, 2026. "Optimizing regional hydrogen energy layout with cost variations in renewable hydrogen production under electricity-hydrogen-carbon coupling," Renewable Energy, Elsevier, vol. 256(PB).
    4. Xue, Qingwen & Wang, Ao & Jiang, Sihang & Wang, Zhichao & Yang, Yingxia & Cheng, Yuanda & Zheng, Zhonghai, 2025. "Stochastic optimization of energy systems configuration for nearly-zero energy buildings considering load uncertainties," Renewable Energy, Elsevier, vol. 243(C).

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