Research on the dynamic price decision model of hydrogen refueling stations considering multiple uncertainties

Hydrogen fuel cell vehicles, with their zero‑carbon advantage, are key to advancing low-carbon transportation. As essential infrastructure, hydrogen refueling stations directly influence their large-scale adoption through hydrogen pricing. However, the hydrogen pricing is influenced by dynamic fluctuations in electricity and carbon market prices, as well as uncertainties in wind and photovoltaic output. Accordingly, this paper proposes a robust multi-objective decision-making model for dynamic hydrogen pricing under the integrated electricity–hydrogen–carbon market integration. First, a hydrogen demand response model for fuel cell vehicles is developed to enable effective source–load interaction and balance hydrogen supply and demand. Second, to maximize hydrogen station revenue and minimize price fluctuations, a dynamic pricing model is developed under a deterministic scenario. Renewable output and electricity price uncertainties are addressed using Confidence Gap Decision Theory (CGDT) and Conditional Value at Risk (CVaR), transforming the deterministic model into the CGDT-CVaR model. Finally, a typical industrial park in Ordos, China, is used for simulation. The results indicate that, compared to traditional model, the proposed CGDT-CVaR model can control the volatility of hydrogen refueling station revenue at 10.87%, reduce hydrogen price volatility by over 40%, and decrease the operational fluctuation of the hydrogen storage system by more than 30%, achieving an optimal balance among economic efficiency, robustness, and price stability. The research findings not only enhance the operational efficiency of hydrogen refueling stations but also provide a theoretical reference for the design of coordinated pricing mechanisms in the electricity‑hydrogen-carbon multi-market.