This study proposes an operational optimization framework for power-to-hydrogen systems that explicitly incorporates the influence of hydrogen price dynamics. Firstly, a fuzzy set is constructed using historical price data to simulate hydrogen price volatility. Subsequently, a seasonal production intensity forecasting mechanism is developed to coordinate hydrogen price volatility with renewable energy variability. Building on this seasonal forecasting, a distributionaly robust optimization model is formulated for the operational scheduling of power-to-hydrogen systems. Case study results demonstrate that the proposed forecasting mechanism enables rational quarterly adjustments of production intensity, and its integration with the distributionaly robust optimization model effectively enhances renewable energy consumption while reducing daily operational costs.

renewable energy  /  hydrogen production  /  uncertainty analysis  /  distributed robust optimization  /  hydrogen price index  /  production intensity