Two-stage robust optimization scheduling for integrated energy systems considering ammonia energy and waste heat utilization

To balance the stability and economic benefits of integrated energy systems (IES) during low-carbon optimization, this paper proposes a two-stage robust optimization scheduling method that considers ammonia energy and waste heat utilization. Firstly, this paper analyzes the Power-to-Ammonia (P2A) operational mechanism and the energy input-output transformation relationship and establishes a Power-to-Ammonia equipment model incorporating waste heat utilization. Subsequently, the low-carbon operational characteristics of the integrated energy system with cooperative operation between Power-to-Ammonia and coal-fired units are explored by integrating Power-to-Ammonia with ammonia-coal co-firing technology. Then, the paper uses an adjustable uncertainty set to describe the variability of renewable generation (RG) and constructs a max-min structured integrated energy system with a two-stage robust optimization scheduling model to minimize the worst-case scenario system operating costs. Finally, the Column-and-Constraint Generation (C&CG) algorithm decomposes the two-stage robust optimization issue into a master problem and sub-problems for the iterative solution. Furthermore, the proposed method is simulated in an actual integrated energy system in northern China. Simulation results indicate that with the intervention of renewable generation uncertainty, the model developed in this study reduces operating costs and carbon emissions by 13.98 % and 20.95 %, respectively, effectively enhancing the capability for low-carbon economic operation. This study provides crucial theoretical support for advancing the low-carbon energy conversion of integrated energy systems.