A Multi-Optimization Method for Capacity Configuration of Hybrid Electrolyzer in a Stand-Alone Wind-Photovoltaic-Battery System
Source abstract
Abstract
The coupling of renewable energy sources with electrolyzers under stand-alone conditions significantly enhances the operational efficiency and improves the cost-effectiveness of electrolyzers as a technologically viable and sustainable solution for green hydrogen production. To address the configuration optimization challenge in hybrid electrolyzer systems integrating alkaline water electrolysis (AWE) and proton exchange membrane electrolysis (PEME), this study proposes an innovative methodology leveraging the morphological analysis of Pareto frontiers to determine the optimal solutions under multi-objective functions including the hydrogen production cost and efficiency. Then, the complementary advantages of AWE and PEME are explored. The proposed methodology demonstrated significant performance improvements compared with the single-objective optimization function. When contrasted with the economic optimization function, the hybrid system achieved a 1.00% reduction in hydrogen production costs while enhancing the utilization efficiency by 21.71%. Conversely, relative to the efficiency-focused optimization function, the proposed method maintained a marginal 5.22% reduction in utilization efficiency while achieving a 6.46% improvement in economic performance. These comparative results empirically validate that the proposed hybrid electrolyzer configuration, through the implementation of the novel optimization framework, successfully establishes an optimal balance between the economy and efficiency of hydrogen production. Additionally, a discussion on the key factors affecting the rated power and mixing ratio of the hybrid electrolyzer in this research topic is provided.
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Research context
OpenAlex topics: Hybrid Renewable Energy Systems · Electric Vehicles and Infrastructure · Advanced Battery Technologies Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Electrical and Control Engineering, North China University of Technology, Shijingshan District, Beijing 100144, China
China Three Gorges Technology Co., Ltd., Xicheng District, Beijing 100032, China
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Haidian District, Beijing 100083, China
Funding
R&D Program of the Beijing Municipal Education Commission
References (34)
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