Research on Source-load Synergy Multi-time Scale Optimal Scheduling Considering Large-scale Renewable Energy Access

To address the significant impact of large-scale integration of new energy into the power system, leading to challenges in accommodating new energy and issues of system operation imbalance, this paper proposes a multi-temporal optimization scheduling method. This method integrates multi-scenario stochastic programming with feedback correction approaches to enhance the integration level of new energy in various scenarios. Firstly, distinct optimization scheduling models are developed for different temporal scales, including day-ahead, intra-day, and real-time scales, considering the operational and response characteristics of different resources, and the interconnection among optimization models across temporal scales is designed. Secondly, the paper conducts multiple comparisons among various storage re-sources, demand response resources, and different scenarios of new energy integration. Through source-load coordination scheduling, this approach achieves economically stable operation of the power system.