Performance analysis of wind-hydrogen energy storage system using composite objective optimization proactive scheduling strategy coordinated with wind power prediction

Xinyi Liu, Zitao Wang, Shuai Xu, Yihe Miao, Jialing Xu, Shanke Liu and Lijun Yu

Energy, 2025, vol. 321, issue C

Abstract: The large-scale deployment of wind energy encounters challenges like randomness, intermittency and fluctuation. Integrating energy storage systems and effective scheduling strategy can mitigate these issues. This paper proposes a composite objective optimization proactive scheduling strategy (COOPSS) integrated with ultra-short-term wind power prediction (WPP) to enhance the performance of the wind-hydrogen energy storage system (W-HESS). The COOPSS model includes four key components: a WPP module, a scheduling strategy, objective functions and parameter optimization. WPP provides projected output, while discrepancies between actual and planned outputs are addressed through a dynamic scheduling strategy to regulate the charge and discharge of the Hydrogen Energy Storage System (HESS). A composite objective function quantifies output accuracy, system fluctuation, and equipment health, with parameter optimization algorithms (Dynamic Information-driven Bayesian Optimization and Sparrow Search Algorithm) refining scheduling parameters. This approach reduces the deviation from the ideal state SoC by 59.4 % compared to real-time scheduling strategies and enhancing fluctuation suppression by 6 % (0.90 MW vs. 0.85 MW). Moreover, compared to wind power without HESS, COOPSS improves power accuracy by 13.9 % (19.76 MW vs. 17.02 MW). Furthermore, WPP accuracy is shown to influence optimization direction, with higher accuracy improving long-term scheduling and state management. COOPSS effectively reduces energy waste and enhances grid stability.

Keywords: Wind-hydrogen energy storage system; Proactive scheduling strategy; Composite objective optimization; Wind power prediction (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:321:y:2025:i:c:s0360544225010588

DOI: 10.1016/j.energy.2025.135416

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