Optimizing wind-solar hydrogen production through collaborative strategy with ALK/PEM multi-electrolyzer arrays

Qinjin Zhang, Di Xie, Yuji Zeng, Yancheng Liu, Heyang Yu and Siyuan Liu

Renewable Energy, 2024, vol. 232, issue C

Abstract: This paper presents an innovative sustainable hydrogen production system integrating solar and wind energy to provide power to alkaline (ALK) and proton exchange membrane (PEM) electrolyzers. On this basis, a novel source and load collaborative optimization strategy is proposed to optimize the hydrogen production system, aiming to address the challenges of the intermittent and variable nature of renewable energy sources. The proposed strategy consists of a classification prediction module using the XGBoost algorithm, which analyzes historical energy generation data to predict optimal electrolyzer operation. Furthermore, the proposed collaborative optimization strategy is able to balance the loads between the electrolyzer arrays, aiming to minimize cold-start situations, prolong steady-state hydrogen production time, and reduce operational variations due to maintenance. The proposed strategy is proved to significantly reduce the standard deviation of the electrolyzer runtime, enhancing the overall system stability, and contributing to the reduction of maintenance frequency. Theoretical analyzes and extensive simulation results validate the effectiveness of the proposed strategy in improving hydrogen production efficiency and sustainability. This work contributes to the integration of renewable energy sources for clean energy production, and provides a practical and effective solution for the urgently needed green hydrogen production.

Keywords: ALK/PEM electrolyzer arrays; Collaborative optimization strategy; Global optimization; Classification prediction (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:232:y:2024:i:c:s0960148124011844

DOI: 10.1016/j.renene.2024.121116

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