On Reliability Assessment of a Battery Energy Storage Systems Supporting PV Plants

Battery energy storage system (BESS) has been highlighted for its possibilities of performing ancillary services to the power system, such as voltage and frequency regulation, power quality, power smoothing, and peak shaving, among others. The BESS is very promising especially associated with renewable energies, such as photovoltaic (PV) and wind. Among some of these ancillary services, this work evaluates the battery lifetime and reliability. The proposed methodology includes the combined analysis of rainflow counting algorithm, Monte Carlo simulation, and nonlinear damage accumulation rule for battery reliability assessment. Monte Carlo simulation is used to approximate the battery reliability estimation of practical applications, by considering stochastic variations in the battery lifetime model. The case study is based on a 100 $\textbf{kW}$ PV system, assessed using a one-year mission profile of solar irradiance and ambient temperature from Goiânla-Brazll associated with a mission profile of 100 $\textbf{kW}$ industrial load. The PV plant is connected to a 440 V grid associated with a BESS that mitigates oscillations of 10% of PV nominal power per minute. The peak shaving service presented a decrease in the battery lifetime by approximately 11 % in relation to the deterministic battery lifetime analysis. On the other hand, the peak shaving presented a decrease in the battery lifetime by approximately 17.4 %. In addition, the pack-level analysis revealed a maximum reduction in the battery lifetime by approximately 30%, when compared to the conventional deterministic battery reliability estimation procedure.