MF_CSA AI based Controlling Technique for Single Phase Converter Output Enhancement at Different Loading Conditions

Renewable and sustainable sources such as SPV systems and WT energy conversion systems are now seen as a promising and growing alternative energy source in view of global emissions and deterioration of the FP. the main objective of the study designing of a solar PV system with varying irradiation in MATLAB/SIMULINK and enhance its output capacity before its integration with the grid. Also, the system has to be made to drive an unbalanced load and dynamic load so that it is capable of handling the change in the power demand of the system. And to design a suitable controller for the multilevel power converter such that it produces better output results than the traditional converter. AI technique has to be incorporated in the converter designing. This work provides a comprehensive design and implementation of power regulatory per phase inverter with proposed MF-CSA (Multi-Function Crow Search Algorithm) optimization controller. The Inverter has been provided with a proposed optimization technique while integrating it with the grid. The voltage output of the system from the modeled solar system with varying irradiation and temperature control is being fed to the inverter for DC to AC conversion