Abstract

Integrating energy storage and hydrogen energy into wind–solar–hydrogen storage microgrids can effectively mitigate the intermittency, volatility, and unpredictability of renewable energy. Aiming at tackling excessively idealized traditional models, this paper establishes a system model for wind–solar–hydrogen storage microgrids by adopting real-world environmental parameters such as wind speed and solar irradiance. To improve the operational performance of the system, an optimal microgrid scheduling method is proposed, which adopts the minimum daily comprehensive operating cost as its core objective. The wind and solar curtailment penalty terms are embedded into the objective function to quantify energy efficiency requirements, and hard constraints including power balance, ramp rate of hydrogen power production, and state of charge (SOC) of energy storage are introduced to guarantee system stability. An improved sparrow search algorithm (ISSA) incorporating a sine function and a golden ratio coefficient is adopted to optimize the position updating process. The objective function is solved so that it satisfies all of the system’s constraints, and the algorithm’s performance is evaluated based on typical daily simulation data. The results demonstrate that the proposed algorithm can effectively optimize the scheduling process and improve the economic efficiency, stability, and overall performance of the system. The total economic benefit generated by the system is increased by 8.48%, which constitutes a remarkable enhancement of the system’s economic efficiency.

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