Improved Cycle Aging Cost Model for Battery Energy Storage Systems Considering More Accurate Battery Life Degradation

Abstract

Battery energy storage systems (BESSs) have been widely used in power grids to improve their flexibility and reliability. However, the inevitable battery life degradation is the main cost in BESS operations. Thus, an accurate estimation of battery aging cost is strongly needed to cover the actual cost of BESSs. The existing models of battery life degradation either are not fully accurate to estimate the actual cost or are not solved easily because of their computation nonlinearity. In this paper, a piece-wise linear battery aging cost model with an accurate estimate of battery life degradation for BESSs is proposed to extend battery life and improve battery profits. In our method, the widely-used Arrhenius law is modified to quantify the battery life degradation affected by the depth of cycle. Further, a nonlinear battery cycle aging cost model is developed by finding the derivative of battery life degradation with respect to discharging power, which indicates the battery life degradation rate due to depth of cycle. To reduce the complexity of computation, a piece-wise linearization method is proposed to simplify the battery cycle aging cost model. Finally, the cycle aging cost model with an accurate estimation of battery life degradation is applied to the optimization dispatch in the day-ahead energy and auxiliary service market. The results show that the error of estimating the battery cycle aging cost of BESSs is less than 5% under proper piece-wise segment numbers. The profits are increased by 27% and the battery life is extended by 11% than the fixed cost method.

Keywords

• Battery energy storage system
• piece-wise linear model
• cycle aging cost
• state of health
• optimization dispatch