Power Flow Management for Off-Grid Photovoltaic-Battery System Using ANN-FL Controller MPPT

Electricity access remains a major issue, especially in isolated areas where traditional power grids are not available. This paper addresses this problem by presenting an in-depth study on controlling the energy flow of an off-grid photovoltaic (PV) and battery system. The system incorporates a sophisticated maximum power point tracking (MPPT) algorithm based on artificial neural networks (ANN) and fuzzy logic (FL). In addition, a charge/discharge management algorithm ensures safe and optimal battery operation. The results highlight the MPPT algorithm's ability to accurately track the point of maximum power for different irradiances. The charge/discharge management algorithm demonstrates its effectiveness in managing energy flow under variable charge and irradiance conditions, ensuring battery safety. In addition, surplus power generation scenarios are explored, detailing the controlled dissipation mechanism and battery recharging strategies.