Comprehensive Evaluation of a PV-Grid Connected System using Quadratic High Gain Boost Converter with Lemur Optimized ANN-Based MPPT Controller

Abstract

The increasing demand for reliable and efficient renewable energy integration requires advanced control and conversion schemes in photovoltaic (PV) systems. This paper presents a comprehensive quantitative evaluation of a PV based grid-connected power generation system incorporating a Quadratic High Gain Boost Converter (QHGBC) and a Lemur Optimized Artificial Neural Network (LO-ANN) based Maximum Power Point Tracking (MPPT) system. The proposed QHGBC ensures high voltage gain and efficient power conversion from PV arrays, while the LOANN-based MPPT provides rapid and accurate tracking of PV maximum power. The bidirectional converter allows seamless charging and discharging of the battery, ensuring stable power delivery to grid applications. Simulation results from MATLAB/Simulink demonstrate significant improvements in energy efficiency as 95%, stability and adaptability, validating the system’s potential for sustainable and reliable grid-connected PV power generation compared to the other recently utilized models.