Optimal scheduling of electricity–hydrogen–ammonia coupled integrated energy system based on uncertain renewable generations

Power-to-ammonia (P2A) technology presents an effective strategy for facilitating the low-carbon transition of integrated energy system (IES), effectively addressing the stochastic and intermittent nature of renewable energy generation. In response to the challenges posed by the increased penetration of renewable energy, this paper develops an optimization scheduling model of IES based on chance constraints within an electricity–hydrogen–ammonia coupled architecture. The model integrates P2A technology, hydrogen blending in gas turbine (GT) and gas boiler (GB), and coal–ammonia co-combustion, while further modeling the dynamic characteristics of the electrolyzer. To account for renewable energy uncertainties, the probability reserve is formulated using chance-constrained programming (CCP). The model is solved using the sequence operation theory, which converts the CCP into a deterministic equivalent model to balance the expected and stochastic outputs of renewable generation. Case studies on four scenarios demonstrate that the proposed model achieves a 5.82% reduction in carbon emissions and a renewable energy utilization rate of 98.3%, outperforming traditional scheduling approaches. Additionally, the optimal system performance is achieved when hydrogen blending ratios reach 16% for GT and 18% for GB. These results underscore the model's effectiveness in enhancing low-carbon operation, maximizing renewable energy utilization, and improving the economic efficiency of IES.