Optimal Scheduling of an Integrated Energy System with Oxygen-Enriched Combustion and Hydrogen–Ammonia Coupling Considering Wind Power Uncertainty

To improve the low-carbon economic operation of integrated energy systems under wind power uncertainty, this paper develops an optimal scheduling model for an integrated energy system coupling oxygen-enriched combustion with hydrogen–ammonia–carbon utilization pathways. The proposed framework integrates oxygen-enriched combustion, electrolysis-based hydrogen production, methanation, hydrogen fuel cells, ammonia synthesis, urea synthesis, captured CO2 utilization, reward–penalty ladder-type carbon trading, and IGDT-based wind power uncertainty scheduling. A deterministic scheduling model is first established to minimize the total operating cost, and Information Gap Decision Theory is then introduced to formulate risk-averse and opportunity-seeking scheduling strategies under wind power uncertainty. Simulation results show that, compared with the post-combustion carbon capture scenario and the conventional coal-fired scenario, the proposed system reduces the total operating cost by 3.37% and 8.03%, respectively, and reduces the wind curtailment cost by 40.2% and 57.0%, respectively. Compared with the post-combustion carbon capture scenario, carbon emissions are reduced by 17.7%. The hydrogen–ammonia–urea chain generates approximately 15.68 × 104 CNY of urea revenue and improves carbon resource utilization. Under an IGDT deviation factor of 0.03, the risk-averse strategy increases the total operating cost by approximately 10.30 × 104 CNY to enhance operational robustness, while the opportunity-seeking strategy reduces the total operating cost by approximately 10.30 × 104 CNY and decreases carbon emissions by 19.6 t. These simulation results verify the effectiveness of the proposed scheduling framework under the designed case study. The proposed framework can improve the low-carbon economy, renewable energy accommodation, carbon resource utilization, and adaptability to wind power uncertainty of the studied integrated energy system.