| Abstract: |
Power quality degradation in modern distribution networks poses significant challenges due to increased penetration of nonlinear loads, renewable energy sources, and power electronic devices. This research investigates intelligent control-based strategies including Artificial Neural Networks, Fuzzy Logic Controllers, and hybrid optimization algorithms integrated with custom power devices such as STATCOM, D-STATCOM, DVR, and UPQC to enhance power quality parameters. The study hypothesizes that intelligent controllers outperform conventional PI controllers in mitigating voltage sags, harmonics, and reactive power issues. Utilizing IEEE 33-bus test system simulations and real-time data analysis, results demonstrate that UPQC with intelligent control reduces Total Harmonic Distortion from 33.26% to 3.11%, voltage sags by 95-100%, and improves voltage stability indices by 92-98%. STATCOM with neural network control achieves THD reduction from 16.25% to 1.62%. The findings establish that intelligent control strategies significantly enhance distribution network reliability, power quality compliance with IEEE 519-1992 standards, and operational efficiency, making them essential for sustainable smart grid development. |
