Design of Modified Luo Converter with Enhanced MPPT Algorithm for PV Systems

Sivaprasad Kollati; Satish Kumar Gudey

doi:10.5935/jetia.v12i59.3640

Autores

Sivaprasad Kollati DEPARTMENT OF ELECTRICAL ENGINEERING, ANDHRA UNIVERSITY, AU-TDR HUB, VISAKHAPATNAM, INDIA. https://orcid.org/0000-0002-7170-7316 (não autenticado)
Satish Kumar Gudey Department of Electrical and Electronics Engineering, Gayatri Vidya Parishad College of Engineering, Visakhapatnam, India https://orcid.org/0000-0003-2444-7467 (não autenticado)

DOI:

https://doi.org/10.5935/jetia.v12i59.3640

Resumo

Photovoltaic (PV) systems are highly sensitive to partial shading conditions, which significantly reduce power extraction efficiency and introduce multiple local maxima in the power–voltage characteristics. This paper proposes a high-gain switched-inductor Modified Luo converter integrated with a Black Widow Optimized Artificial Neural Network (BWO-ANN) based Maximum Power Point Tracking (MPPT) technique for operation under near-zero partial shading conditions. The modified Luo converter enhances voltage gain and reduces current ripple through a switched-inductor configuration, operating in continuous conduction mode (CCM). The voltage conversion ratio is analytically derived using volt-second balance principles. The BWO algorithm optimally tunes ANN parameters to improve tracking speed and convergence accuracy under dynamic irradiance conditions. A high-frequency inverter and isolation transformer provide galvanic isolation between the PV source and DC bus/battery. MATLAB/Simulink validation demonstrates a converter efficiency of 97.79% and MPPT tracking efficiency of 98.96%, outperforming conventional P&O, PSO, and Hill-Climbing techniques. The proposed topology exhibits improved voltage gain, reduced ripple, fast convergence, and stable operation under varying environmental conditions.