Maximum Power Point Tracking for Grid-tied PV System Using Adaptive Neuro-Fuzzy Inference System

This article provides a control approach of a photovoltaic (PV) system connected to the grid (PVSCG). The system consists of a 500 KW PV array, boost converter, and two-level three-phase voltage source inverter (VSI). The DC-DC boost converter in the PV system is controlled via an Adaptive Neuro-fuzzy inference system maximum power point tracking (ANFIS-MPPT) algorithm to optimize the generated power of the PV system. In this technique, the PI control loop is eliminated, and the duty cycle is directly adapted by the MPPT method. Consequently, the MPPT control loop is simplified, as the tuning method for calculating and estimating the gain of the PI controller is eliminated. Also, a comprehensive decoupled current control technique in rotating d-q synchronous reference frame (SRF) is executed to transfer the maximum power extracted to the grid. Simulation results of the system on MATLAB/Simulink software are performed under different levels of solar radiation and cell temperature. The effectiveness of the suggested controller to transfer the generated power to the grid is investigated.