Abstract
The main goal of maximum power point (MPP) tracking control is to extract the maximum photovoltaic (PV) power by finding the optimal operating point under varying atmospheric conditions to improve the efficiency of PV systems. In recent years, the field of tracking the MPP of PV systems has attracted the interest of many researchers from the industry and academia. This research paper presents a comparative study between the modern fuzzy logic based controller and the conventional perturb & observe (P&O) technique. The comparative study was carried out under different weather conditions in order to analyse and evaluate the performance of the PV system. The overall system simulation has been performed using Matlab/Simulink software environment. The simulation results show that the dynamic behaviour exhibited by the modern fuzzy controller outperforms that of the conventional controller (P&O) in terms of response time and damping characteristics.
 
 Keywords: MPPT, photovoltaic system, fuzzy logic control, P&O algorithm.
Highlights
Renewable energy has become an important source of energy due to its several features such as clean and abundant energy
The results demonstrate how the fuzzy logic (FL) maximum power point tracking (MPPT) algorithm reduced the response time of the PV system compared with the perturb and observe (P&O) technique
For the conventional P&O method, the results show the continuous oscillation around the maximum power point (MPP), low tracking speed and tracking in the wrong direction under a fast change of atmospheric conditions
Summary
Renewable energy has become an important source of energy due to its several features such as clean and abundant energy. The most widely used conventional algorithms implemented in the commercial applications are perturb and observe (P&O) (Elbaset, Ali, Abd-El Sattar & Khaled, 2016; Invalid Citation; Mohammed, Devaraj & Ahamed, 2016; Rezk & Eltamaly, 2015) and incremental conductance (IncCond) methods (Rezk & Eltamaly, 2015; Safari & Mekhilef, 2011). The advantages of these methods are their easy implementation and low cost. The fourth section summarises the simulations with Matlab/Simulink, and the last section of this article consists of a conclusion
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