Capacity configuration and control optimization of off-grid wind solar hydrogen storage system

Yuyang Zhao, Yuhuan Zhao, Song Cao, Zhengzheng Zhu and Hexu Sun

Energy, 2025, vol. 324, issue C

Abstract: The configuration and operational validation of wind solar hydrogen storage integrated systems are critical for achieving efficient energy utilization, ensuring economic viability, and maintaining system stability. This study proposed an off-grid multi-energy system capacity configuration and control optimization framework based on the Grey Wolf Optimization (GWO) algorithm, which enhances system revenue through an improved capacity allocation model. The results demonstrate the following: Firstly, the proposed system achieves a significant financial improvement, with an annual revenue increase of 33.79 % compared to a hydrogen production scheme relying solely on wind power without energy storage. Secondly, the adoption of a wind solar complementary hydrogen production approach increases the annual revenue of the system by 33.33 % compared to the single wind power hydrogen production scheme. Furthermore, a system operation control strategy based on the State of Charge (SOC) of lithium batteries is proposed. Using operational data from the Zhangjiakou Chongli wind solar complementary coupling hydrogen production project, the effectiveness of the proposed control strategy is validated, demonstrating its ability to ensure stable system operation. Results show that in wind and solar power excess scenarios, the SOC rises from 45.8 % to 49.8 %, and declines to 47.2 % when there's a power deficit, indicating its potential for peak shaving and valley filling, thereby mitigating fluctuations in wind and solar power output.

Keywords: Wind power; Solar power; Energy storage; Capacity configuration; Power prediction; Grey wolf optimization algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:324:y:2025:i:c:s0360544225016445

DOI: 10.1016/j.energy.2025.136002

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