Abstract:

To address the challenges posed by the volatility of wind and solar power output on virtual power plant scheduling and renewable energy consumption, a coordinated optimization scheduling method for energy storage and multi-type power-to-hydrogen (P2H) facilities is proposed. Firstly, the output of wind and solar power is decomposed into low-, medium-, and high-frequency components using empirical mode decomposition, which are then matched with the respective characteristics of alkaline electrolyzer, proton exchange membrane electrolyzer, and energy storage systems to achieve frequency-division and collaborative consumption of renewable energy. Secondly, an optimization model is constructed to minimize the configuration and operation costs, considering such constraints as electrolyzing powers, state-of-charge of energy storage devices, and power balances. Finally, a three-stage algorithm is designed to determine the optimal scheduling scheme. Simulation results demonstrate that, compared to the collaborative dispatch strategy utilizing a single-type electrolyzer or the strategy combining energy storage with a single-type electrolyzer, the proposed method reduces the curtailment rate to 0.14%, significantly enhancing the consumption efficiency of renewable energy and improving system economics.

Key words: virtual power plant, optimization scheduling, empirical mode decomposition, power-to-hydrogen, collaborative optimization