Hydrogen-Storage Optimization Configuration Method Based on Time-of-Use Electricity Pricing

This study investigates the optimal configuration of hydrogen energy storage systems under time-of-use electricity pricing, proposing a hydrogen-storage co-optimization method based on dynamic pricing to reduce overall operational costs and enhance economic benefits. The research first employs the least squares method to construct a multivariate regression model, fitting 24-hour electricity price data to uncover inherent temporal pricing patterns. Subsequently, an optimization model for hydrogen storage system configuration is established, incorporating comprehensive constraints including equipment capacity, power balance, energy conversion efficiency, and safety/environmental requirements. The particle swarm optimization (PSO) algorithm is applied to determine optimal parameters, achieving the objective of total cost minimization. Through case studies and sensitivity analyses, the feasibility of the proposed method in practical system design is validated. Results demonstrate that the optimized hydrogen storage system effectively reduces operational costs while maintaining grid load balance, delivering economic benefits through peak shaving, valley filling, and "low-storage, high-generation" strategies.