Three-phase Inverter with Fuzzy Logic Control (FLC) based Maximum Power Point Tracking (MPPT) technique for Grid Connected Photovoltaic (GCPV) System

Abstract

The performance of the Photovoltaic (PV) System is dependent upon the environment conditions due to the variation of the solar irradiance and cell temperature. This affects the quality of the output voltage that is generated by the photovoltaic modules. To overcome these challenges, an artificial intelligence approach is implemented into the system. The objective of the proposed work is to develop a boost converter to control the output power generated by the photovoltaic modules by increasing the output power. In order to adjust power factor and power for a three-phase grid inverter system, the boost converter is integrated with a three-phase inverter that uses the Pulse Width Modulation (PWM) control approach. Since it's the most important component of any grid-connected system and enables the source generated to feed into the grid, it evolved to control power to the grid. Therefore, the three-phase inverter with PWM control is proposed to optimize the performance of the PV system. A Fuzzy Logic Control (FLC) is implemented in the system as an artificial intelligence alternative for a PV system that works rapidly, accurately, and efficiently to track the Maximum Power Point (MPP) under varying weather conditions and solar irradiation. By using the FLC, the constraints that come from conventional technologies could be improved and a better grid-connected photovoltaic system be provided. The proposed PV system is modelled and simulated in MATLAB/Simulink. The simulations results are presented.