Maximum power point tracking using perturb and observe, fuzzy logic and ANFIS

Abstract

The main objective of this project is to investigate the performance conventional method of perturb and observe (P&O) and soft computing techniques (fuzzy logic and adaptive neuro-fuzzy inference system) of maximum power point tracking (MPPT) for photovoltaic (PV) module. In this paper, the MSX-64 PV module and boost DC–DC converter are used for simulation and modeling the MPPT system. This work demonstrates the performance of those three types of MPPT techniques, which subjected to a partial shading pattern as well as a non-shaded and shaded of real weather profile. These MPPT techniques are compare in terms of power extracted, MPPT efficiency, rise time, its ability to track global maximum power point (MPP), and the response to varied weather. Simulation results of soft computing MPPT techniques have shown the ability to track the MPP during partial shading conditions and the response to weather changes when non-shaded real weather profile applied to the system. The performance of the conventional P&O based MPPT has depicted the failure of this controller to track the global MPP during partial shading and lack response to real weather changes. The proposed system has simulated using MATLAB SIMULINK.