Ravinder K. Kharb, Md. Fahim Ansari, S. L. Shimi
Maximum power point tracking (MPPT) is used to increase the efficiency of solar photovoltaic (PV) systems under varying weather conditions. Conventional MPPT methods have drawbacks in terms of efficiency, accuracy, and flexibility. This paper presents the design and implementation of a maximum power point tracker that uses adaptive neuro fuzzy inference system (ANFIS). Open loop dc-dc boost converter is interfaced between solar PV module and resistive load. The duty ratio of boost converter is varied using ANFIS and PI controller in order to extract maximum possible power under varying solar irradiance and temperature. The simulated results of proposed tracker show improved performance in terms of oscillations about the maximum power point, speed, high gain and sensitivity to parameter variation. The simulation results of this research are presented to validate the concept