LAUSR

This paper proposes a novel battery wear model for microgrid (MG) energy management applications. This model is based on a popular battery wear model originally proposed for vehicle-to-grid (V2G) applications. The presented model can be easily parameterized to fit the cycle life data of almost any battery and yields the wear cost of a charge/discharge event as function of the variation in the state of charge (SOC) of the battery. This wear model is incorporated into an energy management algorithm to optimize the operation of a grid-connected MG using a day-ahead planning strategy. To test the model, four simulated scenarios are considered in an MG composed of a diesel generator (DG), a photovoltaic (PV) system, a residential load and, naturally, a battery storage system (battery energy storage system (BESS)). The inclusion of the battery wear model leads the optimizer to be more selective about battery usage, cycling the battery at state of charge (SoC) levels that minimized battery wear, effectively prolonging its lifespan.