Abstract :

As Global Renewable Energy Capacity Surpasses 4 TW, Power Quality Challenges Such As Harmonic Distortion, Reactive Power Demands, And Voltage Instability Threaten Modern Grid-tied Solar Photovoltaic (PV) Networks. Mitigating These Issues While Ensuring Grid Compliance Under Nonlinear Loads Requires Advanced Power Conversion And Control Strategies. However, Traditional Grid-connected PV Systems Utilizing Standard Integral Sliding Mode Controllers (ISMC) Suffer From Sluggish Dynamic Responses, DC-link Voltage Fluctuations, And High Total Harmonic Distortion (THD). To Overcome These Limitations, This Paper Proposes An Artificial Neural Network (ANN)-based Sliding Mode Controlled Split-Source Inverter (SSI) Featuring Integrated Reactive Power Compensation And Harmonic Suppression. The ANN Architecture Dynamically Processes Grid Voltages And Currents To Generate Optimized Reference Signals. Concurrently, A Dual-stage Sliding Mode Control (SMC) Framework Regulates The DC-link Voltage On The DC Side While Ensuring Precise Current Tracking And Harmonic Mitigation On The AC Side Via A Modified Space Vector Modulation (MSVM) Technique. Performance Evaluations Demonstrate That The Coordinated ANN–SMC Framework Significantly Minimizes THD, Stabilizes DC-link Voltage, And Superiorly Enhances Grid Resilience Under Volatile Operating Conditions.

Published:

16-7-2026

Issue:

Vol. 26 No. 7 (2026)

Page Nos:

609-622

Section:

Articles

License:

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

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