Abstract :

This Paper Focuses On The Modeling, Design, And Control Of A Single-phase Solar Photovoltaic (PV) Supply System For Gridconnected Applications. The System Employs A Two-stage Power Conversion Process In Which A Step-up Converter (SUC) Is Placed Between The PV Array And The DC Bus Of A Voltage Source Converter (VSC). To Achieve Maximum Power Extraction, A Fuzzy Logic Controller (FLC) Is Implemented For The Switching Of The SUC, Providing Reliable Maximum Power Point Tracking (MPPT) Under Dynamic Solar Conditions. While The FLC-based Approach Ensures Efficient Energy Utilization, Power Quality Remains A Critical Concern Due To Harmonic Distortion. To Overcome This Challenge, The Proposed System Is Extended By Integrating A Neural Network (NN) Controller. The NN Enhances Adaptability And Learning Capability, Enabling Further Reduction Of Total Harmonic Distortion (THD) In The Grid Current While Improving Dynamic Response. The Performance Of The Combined FLC-NN Control Strategy Is Verified Through MATLAB/Simulink Simulations. Results Indicate That The Hybrid Approach Improves MPPT Efficiency, Minimizes THD, And Ensures Compliance With Power Quality Standards. This Makes The System Highly Effective For Residential And Small-scale Solar PV Applications, Supporting Reliable Renewable Energy Integration Into The Grid. Keywords: Solar Photovoltaic System; MPPT; Fuzzy Logic Controller; Neural Network Controller; Step-Up Converter; Voltage Source Converter; THD; Power Quality.

Published:

20-8-2025

Issue:

Vol. 25 No. 8 (2025)

Page Nos:

287-295

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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