Optimal energy management of battery with high wind energy penetration: A comprehensive linear battery degradation cost model

Abstract

Lithium-ion batteries have drawn considerable attention due to their different applications in smart grids. Nevertheless, various factors, including the charging/discharging process, can cause battery capacity degradation and reduce its lifetime. Considering the high investment cost of the battery, employing an appropriate approach to integrate the battery degradation cost into the scheduling problem is vital to optimizing the battery performance. This paper proposes a novel degradation cost model for optimal battery scheduling. A linear model based on the semi-empirical approach is introduced to model the battery capacity degradation process. Moreover, a novel linear algorithm based on the rain-flow algorithm is presented to count complete and incomplete cycles. Then, a degradation cost model is presented based on the amount of battery capacity fade and engineering economics principles. The battery scheduling problem is formulated as a mixed-integer linear programming (MILP) model. In the next stage, a novel approach based on model predictive control (MPC) is utilized to decline the degradation cost and improve battery energy management. The simulation results show that integrating the battery degradation cost into the battery scheduling problem significantly influences the charge/discharge strategy and achieves more benefits for battery owners. In this regard, the proposed scheme can decrease the battery degradation cost and the amount of capacity fade by 31.62% and 37.23%, respectively. Also, considering the battery degradation process in the optimization problem leads to a more optimal and accurate outcome.