Analysis of AI Used in Power Quality Improvement of MPPT Grid Connected PV System

This paper focuses on the modelling and simulation of Maximum Power Point algorithms to Improve Power Quality at different atmospheric condition and using AI Improve efficiency. Grid-connected output systems are made to convert as much solar energy as possible into usable electricity. Artificial intelligence, Artificial Neural Network (ANN) and the Incremental Conductance Technique method are two recommended techniques interface with DC link controller with the reference voltage in a variety of situations. The aim of this paper is to track MPPT from the solar PV array by the proposed AI controller for irradiation changes and comparing results with PO, A single phase grid connected with a photovoltaic (PV) power system wll provide high voltage gain with state model analysis for the control of the system has been presented. First the photovoltaic system is designed and simulated using MATLAB SIMULINK software. The output voltage of a PV array is comparatively low thus high voltage gain is necessary for grid-connection and synchronization. The PV system has been provided with a boost converter which will boost the low voltage of the PV array to high dc-voltage. A steady state model is obtained and is verified with the help of simulation. A full bridge inverter with bidirectional power flow is used as the second power processing stage, which stabilizes the dc voltage and the output current. Further, a maximum-power-point-tracking method is employed in the PV system to obtain a high performance.