Multi-timescale rolling optimization dispatch method for integrated energy system with hybrid energy storage system

Integrated energy system is an important approach to promote large-scale utilization of renewable energy. Under the context of energy market reformation and technology advancement , the economic operation of integrated energy system confronts new challenges, in terms of multiple uncertainties, multi-timescale characteristics of heterogeneous energy, and coordinated operation of hybrid energy storage system . To this end, this paper investigates the multi-timescale rolling optimization of integrated energy system with hybrid energy storage system considering the above challenges. Firstly, a basic framework of an integrated energy system with hybrid energy storage system (consisting of battery and hydrogen storage) is proposed, and the typical devices are modeled in detail. Secondly, the parameters and variables are divided into fast/slow timescale according to dispatch needs, and the multi-timescale problem of heterogeneous energy and the coordinated operation of the hybrid energy storage system can be solved simultaneously through two-stage optimization. Thirdly, the dispatch model is incorporated into the framework of model predictive control , the uncertainty of price, renewable energy and load can be effectively handled. Finally, a case study is conducted using an industrial park in the southern coastal region of China, the comparison with the rule-based method shows 60.65% reduction in the operating cost of hybrid energy storage system, the comparison with robust optimization shows 7.01% reduction in the total cost of the system, thus the feasibility and effectiveness of the proposed method are verified. • The application of HESS in IES is considered and modeled in a more detailed way. • Based on the two-stage approach, the heterogeneous energy multi-timescale scheduling problem and the HESS coordinated operation problem of IES can be solved simultaneously. • The dispatch model is incorporated into MPC for rolling optimization, and multiple uncertainties are effectively handled. • Using an industrial park in the southern coastal region of China as case study, the feasibility and effectiveness of the proposed method are verified.