A PV ramp-rate control strategy to extend battery lifespan using forecasting

Abstract

This study analyses and presents a new ramp-rate control algorithm for smoothing PV power fluctuations, designed to address three fundamental objectives: to reduce battery cycling, to meet minimum storage requirements and to be able to operate, without ramp-rate violations, with real publicly-available forecasting. The algorithm was compared to three benchmark methods and, as a performance limit, also to a hypothetical perfect prediction. Different performance variables were analyzed for all the strategies within a restricted ramp-rate constraint (2%/min): minimum storage requirement, battery power distributions, throughput energy, state of charge (SOC) distributions, degradation (calendar and cycling), expected battery lifespan and levelized cost of energy (LCOE). The proposal proves to be the most cost-effective smoothing technique and the simulation results show that its performance is comparable to the obtained with the use of an assumed perfect prediction.