M. Senthil Kumar, P. Rajakumar and P. Gokul
Abstract
Solar Photovoltaic (PV) exploitation is a significant renewable energy source in our world. The energy converted directly from sunlight through PV panel is not stable due to different environmental conditions. Maximum power point tracking (MPPT) is a technique used for extracting the maximum power from the solar panel. Numerous conventional algorithms are used as MPPT techniques. These conventional methods have limitations like slower response to change in environmental conditions. High-performance soft computing techniques like Fuzzy Logic Control (FLC) and Adaptive Neuro Fuzzy Inference System (ANFIS) can be used as a MPPT for better performance. In this paper, a FLC and ANFIS is proposed to increase the tracking speed and tracking accuracy of the MPPT for a photovoltaic system. The proposed MPPT results are compared with the Perturb and Observation (P&O) MPPT under different weather conditions using MATLAB/Simulink to demonstrate its effectiveness.