Optimal Scheduling Strategy for Hybrid Energy Storage Systems of Battery and Flywheel Combined Multi-Stress Battery Degradation Model

Abstract

The development of microgrid technology and increasing utilization of renewable energy enable hybrid energy storage systems (HESS) to satisfy higher power and energy density requirements. The technology involved in battery energy storage systems (BESS), which is an important part of a HESS, is relatively mature and has a large capacity. The battery degradation issue is critical for the operation of HESS. However, existing studies on scheduling strategies often fail to conduct quantitative analyses or incorporate multiple degradation stress factors. This study proposes an optimal scheduling strategy that quantitatively combines a semi-empirical battery degradation model with multiple stress factors including the state of charge (SOC), depth of cycle (DOC), and time. The piecewise linear aging cost function of BESS is used to simplify the solution to this optimal scheduling problem. Compared to the conventional strategy, the proposed strategy reduces the daily comprehensive cost by 1.10% in a typical scenario. Furthermore, the results demonstrate that the incorporation of a flywheel yield profitable results when the lifespan of the microgrid exceeded 15 y because of its ability to slow battery degradation. Moreover, the proposed strategy provides insight into the SOC scope of the BESS. Consequently, the range of 0.05–0.9 is determined as the best option for reducing operating costs. This study reduces the cost of the microgrid throughout its life cycle and provides guidance for the economic operation of BESS.

Keywords: Hybrid energy storage system, Optimal scheduling, Semi-empirical battery degradation model, Operation cycle cost analysis, Sensitivity analysis