Cost-effective optimization of unified power quality conditioner in wind energy conversion systems using a hybrid EnHBA-GWO algorithm
Year: 2025
Type: article
Abstract: The accelerating deployment of wind energy conversion systems (WECS) in modern power grids has introduced significant challenges in maintaining power quality due to voltage fluctuations, harmonic distortions, and reactive power imbalances. The Unified Power Quality Conditioner (UPQC) offers a comprehensive solution to these challenges. In this study, we propose a novel hybrid optimization approach that integrates the global search capability of the Enhanced Honey Badger Algorithm (EnHBA) with the local refinement strengths of the Grey Wolf Optimizer (GWO) to optimize UPQC parameters in WECS. MATLAB/Simulink simulations are used to evaluate key performance indicators—including energy efficiency, voltage stability, total harmonic distortion (THD), power factor improvement, reliability, and cost-effectiveness. The proposed method achieves 95% energy efficiency, near-unity power factor (0.99), and reduces THD to 5%, ensuring an optimal cost-performance trade-off. These results demonstrate the potential of AI-driven hybrid optimization strategies for enhancing power quality in wind energy applications.
Authors: Shaziya Sultana, Umme Salma
Institution: GITAM University
Language: English
Topic: Power Quality and Harmonics
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4413960706