An Efficient Control Strategy for an Extended Switched Coupled Inductor Quasi-Z-Source Inverter for 3F Grid Connected System

An effective hybrid control technique for an extended switched coupled inductor quasi-Z source inverter for 3F grid-connected photovoltaic (PV) system is proposed in this paper. The proposed hybrid system is a joint implementation of Recalling Enhanced Recurrent Neural Network (RERNN) with Chaotic Henry Gas Solubility Optimization (CHGSO); hence it is named as hybrid RERNN-CHGSO. The main objective of this work is to maximize power extraction to manage the performance of the PV system. The ESCL-quasi-Z-Source inverter modelling is improved to extract maximal power as PV power generation system. The objective function mainly depends on parameters as voltage, current, power, and total harmonic distortion (THD). These parameters are taken into account as input to the proposed hybrid system. When power is shared with the grid, the suggested RERNN-CHGSO system maximizes voltage profile, power delivery, and minimizes THD. Furthermore, the proposed control system minimizes injected power, which generates DC link voltage, current, and frequency conditions. The proposed system is executed on a MATLAB/Simulink platform, and its performance is compared to the existing systems under various conditions.