Novel battery degradation cost formulation for optimal scheduling of battery energy storage systems

Abstract

Battery energy storage systems (BESSs) have gained significant attention for their various applications in power systems. However, the charging and discharging of a battery cause cell degradation, which reduces the battery cycle life. From an economic standpoint, this reduction leads to a battery degradation cost. For the optimal operation of BESSs, the battery degradation cost should be integrated into the optimal scheduling problem while considering the equivalent cycles over the optimization time horizon and the effect of the depth of discharge on the degradation. This paper proposes a new formulation of the battery degradation cost for the optimal scheduling of BESSs. To this end, we define (1) a one-cycle battery cost function based on the cycle life curve and (2) an auxiliary state of charge (SoC) that tracks the actual SoC only upon discharge. By using these, the battery degradation cost can be formulated in a form suitable for a deterministic optimization approach and reflecting equivalent cycles from a rainflow-counting algorithm. The simulation results verify that the proposed method makes the operation of BESSs more economical by rapidly determining the optimal scheduling.