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Energy management strategy for a novel multi-stack integrated hydrogen energy storage system based on hybrid rules and optimization

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  • Lu, Xinyu
  • Gang, Wenjie
  • Cai, Shanshan
  • Tu, Zhengkai

Abstract

To improve the performance of off-grid energy systems, based on a novel multi-stack integrated hydrogen energy storage system, a full life cycle energy management strategy (EMS) with hybrid rules and optimization is proposed. Such a system consists of four PEMECs, four PEMFCs, and a battery pack. The proposed EMS includes online parameter estimation, rule-based primary allocation, and optimization-based secondary allocation. The power is firstly allocated among PEMEC/PEMFC stacks according to a daisy-chained rule based on high efficiency range and multi-stack voltage degradation consistency. The remaining fluctuating power is then preferentially absorbed by the battery using a Q-learning reinforcement learning algorithm. Under stochastic wind power, photovoltaic, and regular load, a comparative analysis with three common EMS validates the feasibility of the proposed EMS. Compared to Q-DC and SOC-DC, the voltage degradation of the multi-stack PEMFCs is reduced by 13.9 %, and the lifetime is improved by 17.2 % and 15.7 %, saving 1315 kg and 1190 kg of hydrogen, respectively. Compared to SOC-PDC and SOC-DC, the lifetime of the battery is improved by 18.8 % and 20.8 %, respectively. The annualized cost of system based on the proposed EMS is the smallest, with reductions of 3 %, 7.4 %, and 9.2 %, respectively.

Suggested Citation

  • Lu, Xinyu & Gang, Wenjie & Cai, Shanshan & Tu, Zhengkai, 2025. "Energy management strategy for a novel multi-stack integrated hydrogen energy storage system based on hybrid rules and optimization," Applied Energy, Elsevier, vol. 381(C).
    • Handle: RePEc:eee:appene:v:381:y:2025:i:c:s030626192402573x
    DOI: 10.1016/j.apenergy.2024.125189
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    1. Yu, Yang & Yu, Qinghua & Luo, RunSen & Chen, Sheng & Yang, Jiebo & Yan, Fuwu, 2024. "Degradation and polarization curve prediction of proton exchange membrane fuel cells: An interpretable model perspective," Applied Energy, Elsevier, vol. 365(C).
    2. Zuo, Jian & Cadet, Catherine & Li, Zhongliang & Bérenguer, Christophe & Outbib, Rachid, 2024. "A deterioration-aware energy management strategy for the lifetime improvement of a multi-stack fuel cell system subject to a random dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    3. Ma, Zhenxi & Cai, Liang & Sun, Li & Zhang, Xiao & Zhang, Xiaosong, 2024. "Thermodynamics and flexibility assessment on integrated high-temperature PEMFC and double-effect absorption heating/cooling cogeneration cycle," Energy, Elsevier, vol. 290(C).
    4. Abdelkader, Abbassi & Rabeh, Abbassi & Mohamed Ali, Dami & Mohamed, Jemli, 2018. "Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy storage," Energy, Elsevier, vol. 163(C), pages 351-363.
    5. Zhou, Su & Fan, Lei & Zhang, Gang & Gao, Jianhua & Lu, Yanda & Zhao, Peng & Wen, Chaokai & Shi, Lin & Hu, Zhe, 2022. "A review on proton exchange membrane multi-stack fuel cell systems: architecture, performance, and power management," Applied Energy, Elsevier, vol. 310(C).
    6. Deng, Zhihua & Chan, Siew Hwa & Chen, Qihong & Liu, Hao & Zhang, Liyan & Zhou, Keliang & Tong, Sirui & Fu, Zhichao, 2023. "Efficient degradation prediction of PEMFCs using ELM-AE based on fuzzy extension broad learning system," Applied Energy, Elsevier, vol. 331(C).
    7. Shi, Wenzhuo & Huangfu, Yigeng & Xu, Liangcai & Pang, Shengzhao, 2022. "Online energy management strategy considering fuel cell fault for multi-stack fuel cell hybrid vehicle based on multi-agent reinforcement learning," Applied Energy, Elsevier, vol. 328(C).
    8. Rocha, C. & Knöri, T. & Ribeirinha, P. & Gazdzicki, P., 2024. "A review on flow field design for proton exchange membrane fuel cells: Challenges to increase the active area for MW applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    9. Hui Su & Chenyu Yang & Meihuan Liu & Xu Zhang & Wanlin Zhou & Yuhao Zhang & Kun Zheng & Shixun Lian & Qinghua Liu, 2024. "Tensile straining of iridium sites in manganese oxides for proton-exchange membrane water electrolysers," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    10. Sattar, Faisal & Ghosh, Sudipta & Isbeih, Younes J. & El Moursi, Mohamed Shawky & Al Durra, Ahmed & El Fouly, Tarek H.M., 2024. "A predictive tool for power system operators to ensure frequency stability for power grids with renewable energy integration," Applied Energy, Elsevier, vol. 353(PB).
    11. Zhou, Su & Zhang, Gang & Fan, Lei & Gao, Jianhua & Pei, Fenglai, 2022. "Scenario-oriented stacks allocation optimization for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 308(C).
    12. Zhang, Gang & Zhou, Su & Gao, Jianhua & Fan, Lei & Lu, Yanda, 2023. "Stacks multi-objective allocation optimization for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 331(C).
    13. Zhang, Hongtao & Li, Xianguo & Liu, Xinzhi & Yan, Jinyue, 2019. "Enhancing fuel cell durability for fuel cell plug-in hybrid electric vehicles through strategic power management," Applied Energy, Elsevier, vol. 241(C), pages 483-490.
    14. Xu, Bin & Li, Xiaoya, 2021. "A Q-learning based transient power optimization method for organic Rankine cycle waste heat recovery system in heavy duty diesel engine applications," Applied Energy, Elsevier, vol. 286(C).
    15. Zhou, Jianhao & Liu, Jun & Xue, Yuan & Liao, Yuhui, 2022. "Total travel costs minimization strategy of a dual-stack fuel cell logistics truck enhanced with artificial potential field and deep reinforcement learning," Energy, Elsevier, vol. 239(PA).
    16. Becker, F. & Cosse, C. & Gentner, C. & Schulz, D. & Liphardt, L., 2024. "Novel electrochemical and thermodynamic conditioning approaches and their evaluation for open cathode PEM-FC stacks," Applied Energy, Elsevier, vol. 363(C).
    17. Burin Yodwong & Damien Guilbert & Matheepot Phattanasak & Wattana Kaewmanee & Melika Hinaje & Gianpaolo Vitale, 2020. "Faraday’s Efficiency Modeling of a Proton Exchange Membrane Electrolyzer Based on Experimental Data," Energies, MDPI, vol. 13(18), pages 1-14, September.
    18. Xu, Bin & Shi, Junzhe & Li, Sixu & Li, Huayi & Wang, Zhe, 2021. "Energy consumption and battery aging minimization using a Q-learning strategy for a battery/ultracapacitor electric vehicle," Energy, Elsevier, vol. 229(C).
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