Microgrid Multi-Time Scale Rolling Optimization and Modification Scheduling Considering the Decision of Air Conditioning Users

Demand response is an effective load management strategy that helps balance power supply and demand and improve the stability and reliability of the power grid. Air conditioning plays a crucial role in power demand response. However, air conditioning users’ decisions are highly uncertain, leading to a significant deviation in the scheduling process. Therefore, this paper proposes a microgrid multi-time scale rolling optimization and modification scheduling considering the decision of air conditioning users. Firstly, to maximize the dispatchability and flexibility of air conditioning loads, the dynamic decisions of air conditioning users are considered, and a virtual energy storage model for variable-frequency air conditioning is developed. Secondly, by integrating optimization strategies across multiple time scales, a day-ahead scheduling model is proposed to minimize microgrid operational costs. Then, considering the deviation between the day-ahead time and intra-day time, as well as the dynamic decision probability of air conditioning users, the intra-day rolling modification method of microgrid penalty cost minimization is proposed, and the scheduling plan is corrected in real-time through this rolling strategy. Finally, the effectiveness of the microgrid integrated demand response and multi-time scale optimization strategy is demonstrated through simulation examples and comparative analysis.