Triple-level cost-effective sizing optimization for solar-powered hybrid hydrogen system with PEM and alkaline electrolyzers

Haowen Hu, Fengxiang Chen, Yejing Xu, Huan Ye, Zhipeng Hou, Bo Zhang and Xiuxiang Chen

Energy, 2025, vol. 334, issue C

Abstract: Proton exchange membrane water electrolyzer (PEMWE) are known for their rapid response but high cost, while alkaline water electrolyzer (AWE) are inexpensive yet exhibit slower cold-start and power response characteristics. By integrating both types, the balance between quick response and low cost can be achieved, enhancing the electrical efficiency of hydrogen production. This study focuses on optimizing the cost-effective sizing of hybrid hydrogen system (HHS) that combines PEMWE and AWE, powered by solar energy. A triple-level methodology incorporating thermal modeling and control, power scheduling, and sizing optimization is designed. The modeling and control framework considers the thermal behavior of PEMWE to enhance lifetime, and the cold-start characteristics of AWE to accurately simulate the cold-start process and time delays. The study utilizes a first-in-first-out (FIFO) scheduling approach to manage a solar-powered HHS and compares it with frequency decoupling (FD) strategy results. Subsequently, a genetic algorithm is utilized to optimize the configuration of PEMWE and AWE based on a year-long operational simulation across four different situations. The results show the HHS optimized by the FIFO strategy demonstrates a 25.4 % lower annual investment cost than the system with a fixed 2:1 configuration (Situation 1) and a 38.9 % lower cost compared to the system optimized by FD strategy (Situation 1). Additionally, the HHS optimized by the FIFO strategy exhibits a 3.7 % higher annual economic performance than the system with a fixed 2:1 configuration (Situation 4) and a 23.2 % higher performance compared to the system optimized by FD strategy (Situation 4).

Keywords: Sizing optimization; Hybrid electrolyzers; Thermal management; Power scheduling; Genetic optimization algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:334:y:2025:i:c:s036054422503289x

DOI: 10.1016/j.energy.2025.137647

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