Fuzzy Logic-Based Proactive Operation Strategy for PV-ESS Reflecting Future Weather Forecasts

This paper presents a cost-effective operation strategy for integrating photovoltaic (PV) generation with an energy storage system (ESS). The approach interprets future solar Irradiance forecasts using fuzzy logic to dynamically set the target state of charge (SOC) of the battery. By adjusting the SOC target according to predicted sunlight, the ESS can be proactively managed to prevent overcharging and over-discharging. Unlike artificial intelligence methods, the fuzzy membership functions provide a clear, rule-based connection between irradiance predictions and SOC targets, ensuring both transparency and ease of implementation. A constrained optimization problem is further formulated with battery current as the decision variable to minimize electricity costs and power losses, yielding an optimal current profile. Simulation results show that the proposed method lowers electricity expenses compared with conventional peak-shaving strategies and reduces deep cycling, thereby extending battery life.