Low-Carbon and Optimized Dispatching of Regional Integrated Energy Systems, Taking into Account the Uncertainties of Wind–Solar Power and Dynamic Hydrogen Prices

Integrated energy systems are central to advancing efficient energy utilization and low-carbon transformation. In the current context, the inherent variability of high-penetration renewable sources (e.g., wind and solar) and the volatility of multi-energy loads (electricity, gas, heat, hydrogen) introduce significant uncertainties into integrated energy system dispatch from both supply and demand sides. To enhance renewable energy integration, operational economy, and low-carbon performance, this paper proposes a low-carbon optimal dispatch method for regional integrated energy systems that considers wind–solar uncertainty and dynamic hydrogen pricing. The significance of this study lies in addressing issues such as the difficulty of fixed hydrogen prices in guiding demand-side responses, insufficient incentives from traditional carbon pricing mechanisms, and the poor robustness of dispatching schemes under uncertainties. The price is dynamically adjusted according to the output of renewable energy and the level of hydrogen storage needed to stimulate the elastic response of hydrogen load. Secondly, a mechanism was proposed to constrain the carbon cost. Finally, the uncertainties stemming from wind and solar power output and multiple loads are addressed by employing fuzzy opportunistic constrained programming. Comparative analysis results of different scenarios indicate that the proposed strategy cuts down the system’s carbon emissions by 12.48%, increases hydrogen sales revenue by 9.96%, and lowers operating costs by 13.69%. Research has confirmed that this method not only enhances the system’s adaptability to uncertainty but also effectively balances the system’s economic efficiency with a cleaning objective. The novelty of this paper resides in the integration of dynamic hydrogen pricing mechanisms, tiered carbon trading schemes, and fuzzy opportunistic constrained programming for the first time, offering an innovative solution for the economic operation of regional integrated energy systems under uncertain scenarios.