Double-Layer Optimization Evaluation Considering the Health of Energy Storage Batteries

With the wide application of renewable energy and the increase of energy storage demand, the optimization of energy storage system configurations to enhance economic efficiency has emerged as a central focus in the research on energy storage systems. In this paper, a double-layer optimal configuration evaluation model that takes into account the condition of energy storage system is proposed, which firstly establishes an energy storage battery health status model and combines it with the strategies for charging and discharging the energy storage system. The upper-layer optimization model is then established with the objective of maximizing the net present value (NPV). A mixed- integer linear programming method is employed to solve this upper-layer model. Additionally, a lower-layer whole-life cycle evaluation model is developed, utilizing the AHP-entropy weight-coefficient of variation method grounded in game theory to address the lower-layer model. Finally, using a business park as a case study, this analysis demonstrates that taking into account the health condition of energy storage batteries can significantly reduce the overall life cycle cost.