POWER QUALITY ENHANCEMENT IN PV–PMSG GRIDS USING WHALE OPTIMIZATION-TUNED STATCOM

The increasing penetration of renewable energy sources such as photovoltaic (PV) systems and permanent magnet synchronous generators (PMSGs) in distribution networks has introduced significant power quality challenges. This paper proposes a novel approach for improving the power quality of a grid-connected hybrid renewable system by employing a Static Synchronous Compensator (STATCOM) whose Proportional-Integral (PI) controller parameters are optimally tuned using the Whale Optimization Algorithm (WOA). Three distinct loading conditions — moderate load, heavy load surge, and light load — are considered to evaluate the system’s dynamic and steady-state performance. The optimized STATCOM effectively mitigates voltage dips, reduces power oscillations, and improves system transient response. Detailed time-domain simulations demonstrate that the proposed WOA-tuned STATCOM significantly enhances voltage stability, minimizes peak overshoot, improves settling time, and reduces harmonic distortions. Furthermore, the system performance under different loading scenarios confirms the superiority of the WOA-based optimization in stabilizing the hybrid renewable grid interface. The study also outlines directions for future expansion by considering nonlinear and unbalanced load impacts on system dynamics.

Authors

Publication Details

Journal
International Journal of Apllied Mathematics
Published
2025-10-15
DOI
https://doi.org/10.12732/ijam.v38i6s.404
Primary Topic
Power Line Communications and Noise
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

POWER QUALITY ENHANCEMENT IN PV–PMSG GRIDS USING WHALE OPTIMIZATION-TUNED STATCOM

Ankit Patel
International Journal of Apllied Mathematics
Power Line Communications and Noise
article

POWER QUALITY ENHANCEMENT IN PV–PMSG GRIDS USING WHALE OPTIMIZATION-TUNED STATCOM

Ankit Patel
article en

Abstract

The increasing penetration of renewable energy sources such as photovoltaic (PV) systems and permanent magnet synchronous generators (PMSGs) in distribution networks has introduced significant power quality challenges. This paper proposes a novel approach for improving the power quality of a grid-connected hybrid renewable system by employing a Static Synchronous Compensator (STATCOM) whose Proportional-Integral (PI) controller parameters are optimally tuned using the Whale Optimization Algorithm (WOA). Three distinct loading conditions — moderate load, heavy load surge, and light load — are considered to evaluate the system’s dynamic and steady-state performance. The optimized STATCOM effectively mitigates voltage dips, reduces power oscillations, and improves system transient response. Detailed time-domain simulations demonstrate that the proposed WOA-tuned STATCOM significantly enhances voltage stability, minimizes peak overshoot, improves settling time, and reduces harmonic distortions. Furthermore, the system performance under different loading scenarios confirms the superiority of the WOA-based optimization in stabilizing the hybrid renewable grid interface. The study also outlines directions for future expansion by considering nonlinear and unbalanced load impacts on system dynamics.

International Journal of Apllied MathematicsVol. 38(6s)
Openalex Percentile: Top 71%
Power Line Communications and Noise
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.

POWER QUALITY ENHANCEMENT IN PV–PMSG GRIDS USING WHALE OPTIMIZATION-TUNED STATCOM — Ankit Patel · International Journal of Apllied Mathematics (2025) | TGRS Research Map | TGRS