Hydrogen energy leads us in an important direction in the development of clean energy, and the comprehensive utilization of hydrogen energy is crucial for the low-carbon transformation of the power sector. In this paper, the demand for hydrogen energy in various fields is predicted based on the support vector regression algorithm, which can be converted into an equivalent electrical load when it is all produced from water electrolysis. Then, the investment costs of power generators and hydrogen energy equipment are forecast considering uncertainty. Furthermore, a planning model is established with the forecast data, initial installed capacity and targets for carbon emission reduction as inputs, and the installed capacity as well as share of various power supply and annual carbon emissions as outputs. Taking Gansu Province of China as an example, the changes of power supply structure and carbon emissions under different scenarios are analysed. It can be found that hydrogen production through water electrolysis powered by renewable energy can reduce carbon emissions but will increase the demand for renewable energy generators. Appropriate planning of hydrogen storage can reduce the overall investment cost and promote a low carbon transition of the power system.

To achieve more precise and regionally adaptive emission control, this study develops a dual-control framework that simultaneously constrains both total carbon emissions and pollutant concentration levels. Regional environmental heterogeneity is incorporated into the dispatch of generating units to balance emission reduction and operational efficiency. Based on this concept, a regional carbon emission allowance allocation model is constructed by integrating ecological pollutant concentration thresholds. A multi-source Gaussian plume dispersion model is further developed to characterize the spatial and temporal distribution of pollutants from coal-fired power units. These pollutant concentration constraints are embedded into an environmental–economic dispatch model of a coupled electricity–hydrogen–carbon system supported by hybrid storage. By optimizing resource use and minimizing environmental damage at the energy-supply stage, the proposed model provides a low-carbon foundation for the entire industrial production cycle. This approach aligns with the sustainable development paradigm by integrating precision environmental management with circular economy principles. Simulation results reveal that incorporating pollutant concentration control can effectively reduce localized environmental pressure while maintaining overall system economy, highlighting the importance of region-specific environmental capacity in enhancing the overall environmental friendliness of the industrial chain.