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.
This paper proposes a combined system of three-phase four-wire shunt active power filter (SAPF), and photovoltaic generator (PVG), to solve the power quality problems such as harmonic currents, poor power factor, and unbalanced load. In addition, the proposed system can inject the issued energy from the PVG into the utility grid. To increase the efficiency of the PVG and extract the maximum photovoltaic (PV) power under variable atmospheric conditions, a maximum power point tracking (MPPT) technique based on perturb and observe (P&O) is implemented in the DC/DC boost converter. The effectiveness of the proposed PVG-SAPF (PVG and SAPF) based on the use of synchronous reference frame theory (SRF theory) under unbalanced nonlinear load. The proposed PVG-SAPF is validated through numerical simulations using Matlab/Simulink software. The simulation results show the effectiveness of the proposed PVG-SAPF.
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