Improvement of Rooftop Solar Panels Efficiency using Maximum Power Point Tracking Based on an Adaptive Neural Network Fuzzy Inference System

Rooftop solar panels are a strategy for achieving Indonesia's renewable energy goals, but their non-linear characteristics make them difficult to control, especially in the face of extreme weather changes. An effective controller is needed optimize power output panels. This study proposes Maximum Power Point Tracking (MPPT) based on an Adaptive Neural network Fuzzy Inference System (ANFIS) address this control problem. The capacity rooftop 3,430-Watt peak (Wp) and they connected 220-Volt (V) grid system. system designed, simulated, analyzed using Simulink model. proposed ANFIS MPPT compared Perturb Observe (P&O) no systems. simulation results show that rapid changes irradiation temperature, efficiency better than P&O by 0.4523 0.1115%, respectively.