Adaptive Neuro-Fuzzy Energy Management of Grid-Connected PV Systems with Hybrid Storage for Voltage and Frequency Stability

The paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) - smart energy management scheme for a grid-connected hybrid power conversion system integrating photovoltaic (PV) generation, battery, and supercapacitor storage. The devised control maintains stability of the DC-side voltage stability, smooths PV power fluctuations, and ensures reliable operation under variable load and irradiance. Synergistic storage system utilizes a battery for long-term energy balancing and a supercapacitor for transient stabilization. The ANFIS controller adaptively manages power sharing between PV, grid, and storage elements, enhancing power quality and reducing Harmonic content ratio. Simulation results Evident that the proposed ANFIS-based Controller sustains THD at 0.24%, outperforming conventional PI and fuzzy controllers in dynamic response, settling time, and voltage regulation.