An Optimal SG-MFO Based Renewable Energy Source Power Quality Improvement Using UPQC in DPFC System

This work proposes an optimal Stochastic Gradient Moth Flame Optimization (SG-MFO) based renewable energy source power quality improvement using Unified Power Quality Conditioner (UPQC) in a Distributed Power Flow Controller (DPFC) system. Power quality issues have become increasingly prevalent due to the growing use of non-linear loads and power electronics devices. The integration of renewable energy sources (RES) into the grid further exacerbates these challenges. To address these concerns, this research introduces a novel approach combining UPQC with an SG-MFO algorithm to enhance power quality in a WSCC 3-machine 9 bus system. The SG-MFO algorithm is employed to optimize the PID controller parameters and improve the Maximum Power Point Tracking (MPPT) mechanism. The proposed system incorporates a photovoltaic (PV) source and aims to mitigate harmonics, voltage sags, and swells while maximizing energy extraction from renewable sources. Experimental results demonstrate significant improvements in grid voltage and current Total Harmonic Distortion (THD). The grid current THD was reduced from 11.2% to 3.03%, while the grid voltage THD decreased from 7.39% to 1.15% after UPQC activation. The system also effectively compensated for voltage sags and swells, maintaining stable grid voltage and current. These results highlight the efficacy of the proposed SG-MFO based UPQC-DPFC system in enhancing power quality.

Authors

Institutions

Publication Details

Published
2025-04-04
DOI
https://doi.org/10.1109/icaeca63854.2025.11012272
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Optimal SG-MFO Based Renewable Energy Source Power Quality Improvement Using UPQC in DPFC System

M Mathankumar, T. Dineshkumar, P. Thirumoorthi
Advanced Battery Technologies Research
article

An Optimal SG-MFO Based Renewable Energy Source Power Quality Improvement Using UPQC in DPFC System

M Mathankumar, T. Dineshkumar, P. Thirumoorthi
article en

Abstract

This work proposes an optimal Stochastic Gradient Moth Flame Optimization (SG-MFO) based renewable energy source power quality improvement using Unified Power Quality Conditioner (UPQC) in a Distributed Power Flow Controller (DPFC) system. Power quality issues have become increasingly prevalent due to the growing use of non-linear loads and power electronics devices. The integration of renewable energy sources (RES) into the grid further exacerbates these challenges. To address these concerns, this research introduces a novel approach combining UPQC with an SG-MFO algorithm to enhance power quality in a WSCC 3-machine 9 bus system. The SG-MFO algorithm is employed to optimize the PID controller parameters and improve the Maximum Power Point Tracking (MPPT) mechanism. The proposed system incorporates a photovoltaic (PV) source and aims to mitigate harmonics, voltage sags, and swells while maximizing energy extraction from renewable sources. Experimental results demonstrate significant improvements in grid voltage and current Total Harmonic Distortion (THD). The grid current THD was reduced from 11.2% to 3.03%, while the grid voltage THD decreased from 7.39% to 1.15% after UPQC activation. The system also effectively compensated for voltage sags and swells, maintaining stable grid voltage and current. These results highlight the efficacy of the proposed SG-MFO based UPQC-DPFC system in enhancing power quality.

SRM Institute of Science and Technology (IN)
Affordable and clean energy
Openalex Percentile: Top 87%
Advanced Battery Technologies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.