Multi-time scale optimal scheduling of integrated energy systems with multiple integrated demand responses

In a bid to attain the carbon peaking and carbon neutrality objectives, integrated energy systems (IES) have seen extensive promotion and application. However, existing studies have not fully utilized the multi-timescale nature of integrated demand response (IDR), which limits the broader participation of IDR resources in system operation coordination. To further enhance the capability of IDR in optimizing IES operations and reduce system operating costs, this study puts forward a multi-timescale optimal scheduling model for IES with IDR taken into account. First, based on the multi-timescale characteristics of IDR, models for different types of IDR resources are established to address system requirements across varying timescales. The day-ahead stage focuses on the economic operation of IES over a scheduling cycle, formulating an economically optimal day-ahead dispatch plan while incorporating a price-based demand response model. In the intraday scheduling stage, the correlations and complementarities of cooling, heating, and electricity across different timescales are considered. This stage is divided into long and short timescales to solve the adjusted outputs of cooling, heating, and electrical equipment, while incorporating a heat-electricity substitutable demand response model and an interruptible demand response model for electrical loads. Finally, case simulations demonstrate that compared to traditional models, the proposed model can effectively exploit demand response potential, narrow the gap between peak and valley loads, and lower system operating costs.