Predictive energy management strategy for battery energy storage considering battery degradation cost

Abstract This study proposes a novel predictive energy management strategy to integrate the battery energy storage (BES) degradation cost into the BES scheduling problem and address the uncertainty in the energy management problem. As the first step, the factors affecting the BES calendar aging and cycle aging are linearly modelled. Furthermore, a linear algorithm is provided to calculate the BES cycle aging due to the BES complete and incomplete cycles. Subsequently, a novel approach to estimating the BES degradation cost function according to the BES specifications and degradation process is presented. Finally, taking into account the BES degradation cost model, the proposed predictive energy management strategy framework is implemented on an integrated photovoltaic and BES system to evaluate the applicability and efficiency of the proposed scheme in integrating the BES degradation cost in the energy management problem. The numerical simulation results indicate that integrating the BES degradation cost into the energy management problem significantly affects the BES charge/discharge strategy. Moreover, comparing the proposed predictive energy management strategy with a simple one, it is verified that the provided approach could decrease the BES capacity fade and degradation cost by 5.06% and 4.67%, respectively, and increase the photovoltaic farm profit by 1.10%.