Optimization and performance analysis of integrated energy systems considering hybrid electro-thermal energy storage

As the integration and complexity of integrated energy systems (IES) continue to increase, the synergistic optimization of operation strategies and configuration schemes is encountering formidable challenges. This study presents a novel IES planning model that enables hierarchical optimization of operation strategies and configuration schemes, considering hybrid electric and thermal energy storage. In the initial phase, a population intelligence approach is employed to optimize the configuration scheme of the system. Subsequently, in the second stage, mathematical planning methods are utilized to optimize the operation strategy of the system, thereby further enhancing its performance. The case study reveals that the proposed hierarchical configuration and operation optimization model significantly improves the system's independence, energy, environmental, and economic performance compared to multiple operational strategies such as following electric load (FEL), following thermal load (FTL), and following hybrid load (FHL). Specifically, in comparison to rule-based operation strategies, the proposed model achieves a maximum annual cost-saving rate (ACSR), primary energy saving rate (PESR), pollution emission reduction rate (PERR), and performance comprehensive index (PCI) of 22.45 %, 35.73 %, 35.77 %, and 30.07 %, respectively. Additionally, through an in-depth comparative analysis of four scenarios, namely hybrid electro-thermal energy storage, electrical energy storage, thermal energy storage, and no energy storage, it is found that hybrid electro-thermal energy storage technology exhibits significant advantages in terms of enhancing energy efficiency, environmental friendliness, and operational independence of the IES.