Research on Capacity Configuration Optimization of Integrated Energy System Based on Hybrid Energy Storage

Integrated energy system (IES) has achieved very rapid development due to the high energy utilization rate and low carbon emission rate. This paper proposes an IES for a salt chemical industrial park in Jiangsu Province, which includes a hybrid energy storage system coupled with lithium battery energy storage, compressed air energy storage, hydrogen storage and heat storage, and a high proportion of renewable energy. The energy model of the system was established. Furthermore, considering the economy and environmental protection of the system comprehensively, with the goal of optimizing the economy and environmental protection, Non-dominated Sorting Genetic Algorithm-II (NSGA- II) is adopted to obtain the Pareto front solution set. The optimal solution of the Pareto front is obtained through Technique Order Preference by Similarity to an Ideal Solution (TOPSIS). The validity and correctness of the calculation results of the system were verified through three typical days. The research results show that the capacity allocation optimization method of the IES based on hybrid energy storage proposed in this paper effectively improves the utilization rate of renewable energy, achieves the lowest economic cost and carbon emissions, and enhances the economy and environmental protection of the system. The research offers robust theoretical underpinnings for the development of large-scale, low-carbon smart energy demonstration projects.