Stochastic scheduling optimization of integrated energy system incorporating power and ammonia energy storages for cost-effective and flexible operation

Integrating renewable-power-to-ammonia storage into conventional coal-powered combined heat and power system is crucial to realize cost-effective and stable operation under low-carbon development goal. However, the thermoelectric coupling characteristics and complex structures pose significant challenges in achieving optimal scheduling and flexibility. This paper proposes an integrated energy system that combines power-to-ammonia with electrical energy storage to enhance system flexibility while reducing carbon emissions. Combining to the penetration mechanism of renewable energy, a stochastic scheduling optimization model for the system's cost-effective and flexible operation is proposed to minimize total operation cost including operation cost, carbon cost, and environmental cost. A scenario analysis method, integrating Latin hypercube sampling with a scenario 0–1 reduction algorithm, is employed to characterize the uncertainty of renewable power. A case study is implemented to validate the proposed method. The simulation results demonstrate that the proposed system reduces fuel costs by 6.59 % compared to traditional integrated system. The coordinative integration and operation of power and ammonia storages reduce renewable energy curtailment by 5.98 % and CO 2 emissions by 6.6 %. The operation areas of combined heat and power is increased by 39.88 % and the system operating flexibility increases. The constructed system and operation strategies provide effective methods to retrofit traditional coal-fired power plants, enabling them to incorporate more renewable energy penetration. • An IES model combining P2A technology and EES is proposed. • Energy scheduling is optimized through P2A coordination. • Latin hypercube sampling and 0–1 clustering capture renewable energy uncertainty. • Feasible system flexibility with operation regions is analyzed. • Ammonia-coal co-firing analysis shows a 6.6 % reduction in carbon emissions.