A bi-level scheduling strategy for integrated energy systems considering integrated demand response and energy storage co-optimization

Abstract

In the context of China's “double carbon” commitment to the world, the introduction of integrated demand response mechanism and compressed air energy storage system into the traditional energy system is important to improve its structure, promote the interaction of multiple heterogeneous energy sources, and improve energy conversion efficiency. As such, in this study, we constructed an upper-layer capacity configuration model aiming to optimize the operating costs of compressed air energy storage systems during the planning period and subsequently integrated a heterogeneous energy network operation and China's certified emission reduction constraints under various operating scenarios. We established a lower-level optimal scheduling model with the optimization objective of minimizing the energy purchase, operation, maintenance, integrated demand response subsidy, and carbon trading costs. Finally, the KKT condition and the Big M method were used to solve this two-tier optimization problem. The comparative analysis of the three schemes showed that, under the consideration of the integrated demand response mechanism and the equipped compressed air energy storage system, the total operating cost of the system was reduced by an average of 2.28 %, the carbon emission was reduced by an average of 7.17 %, the profit from the sale of surplus carbon emission credits increased by an average of 16.7 %, and the energy storage capacity was reduced by approximately 39 %. Thus, this method effectively reduced the capacity of the energy storage system and significantly improved its reliable, economic, and low-carbon operation.