Day-Ahead Optimization and New Energy Integration Capacity Assessment of Integrated Energy Systems.

This paper analyzes the flexibility characteristics of integrated energy systems and constructs a day-ahead optimization scheduling model for integrated energy systems. Based on this, the flexibility of the integrated energy system is quantitatively evaluated. Firstly, considering the uncertainty of renewable energy generation in the park, a min-max-min two-stage three-layer robust day-ahead optimization scheduling model is constructed. In the first stage, the operating range of the equipment is determined, and in the second stage, considering the uncertainty of renewable energy generation in the park, the specific scheduling plan of the equipment is obtained based on the operating range determined in the first stage. The optimal operating range of the equipment and the corresponding scheduling arrangement for specific scenarios are obtained through the collaborative optimization between the two-stage models. Finally, the flexibility of the integrated energy system park is evaluated based on the optimization results of the day-ahead scheduling model. The proposed model in this paper is essentially a two-stage three-layer MILP problem, solved using a nested column and constraint generation algorithm combined with KKT conditions. Finally, the effectiveness of the proposed method is verified through numerical examples.