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Model simulation and multi-objective capacity optimization of wind power coupled hybrid energy storage system

Author

Listed:
  • Hu, Song
  • Yang, Hao
  • Ding, Shunliang
  • Tian, Zeke
  • Guo, Bin
  • Chen, Huabin
  • Yang, Fuyuan
  • Xu, Nianfeng

Abstract

Wind and hydrogen energy storage systems are increasingly recognized as significant contributors to clean energy, driven by the rapid growth of renewable energy sources. To enhance system efficiency and economic feasibility, a model of a wind power-integrated hybrid energy storage system with battery and hydrogen was developed using TRNSYS. The system is optimized using the Non-dominated Sequential Genetic Algorithm for multi-objective capacity allocation, emphasizing economy, reliability, and energy consumption rates. Based on the Pareto frontier diagram, optimal solutions are derived under varying objective weights, and representative cases are selected for comparative analysis. The impact of varying equipment capacities on the system is thoroughly investigated. Lastly, the constructed model and operational strategy are validated through quantitative energy flow analysis of each system component. Results indicate that the electrolyzer capacity significantly affects the system's power abandonment rate, while the battery capacity predominantly influences the system's life cycle cost and loss of power supply probability. In this system, the primary role of the battery storage system is to supply electricity to loads as needed, filling over 78 % of the deficit independently. The hydrogen storage subsystem can absorb over 55 % of wind power annually and sell hydrogen converted from more than 40.9 % of wind power promptly and on demand for revenue. This study offers valuable insights into designing the configuration and operational strategy of a renewable energy-coupled hydrogen energy storage system, along with guidance for optimizing its multi-objective capacity allocation.

Suggested Citation

  • Hu, Song & Yang, Hao & Ding, Shunliang & Tian, Zeke & Guo, Bin & Chen, Huabin & Yang, Fuyuan & Xu, Nianfeng, 2025. "Model simulation and multi-objective capacity optimization of wind power coupled hybrid energy storage system," Energy, Elsevier, vol. 319(C).
    • Handle: RePEc:eee:energy:v:319:y:2025:i:c:s0360544225005298
    DOI: 10.1016/j.energy.2025.134887
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    References listed on IDEAS

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    1. Dong, Haoxin & Shan, Zijing & Zhou, Jianli & Xu, Chuanbo & Chen, Wenjun, 2023. "Refined modeling and co-optimization of electric-hydrogen-thermal-gas integrated energy system with hybrid energy storage," Applied Energy, Elsevier, vol. 351(C).
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