JOURNAL OF RENEWABLE ENERGY SYSTEMS AND MANAGEMENT
Volume 1, Numéro 1, Pages 40-48
2025-12-21
Design Of A Novel Hybrid Grey Wolf Equilibrium Optimizer For Mppt To Enhance The Efficiency Of Solar Photovoltaic Systems
Authors : Abdelmalek Feriel . Afghoul Hamza . Krim Fateh . Zabia Djallaleddine . Krm Salah Aniss . Bouzidi Belgacem Med Nassim . Boukhdanna Alla Eddine .
Abstract
This study introduces an innovative approach for Maximum Power Point Tracking (MPPT) utilizing Grey Wolf Equilibrium Optimizer (GWEO). The method combines the exploration mechanisms of Grey Wolf Optimizer (GWO) with the adaptive features of the Equilibrium Optimizer (EO) to strengthen global search performance and enhance convergence speed. To assess its effectiveness, the proposed GWEO method is examined under diverse and dynamic Partial and Dynamic Shading Conditions (PSCs and DSCs). Its tracking accuracy and efficiency are benchmarked against conventional MPPT strategies including GWO and Particle Swarm Optimization (PSO) across two representative shading scenarios. Simulation experiments in MATLAB/Simulink confirm revealing that the hybrid optimizer is able to reliably detect global maximum power point (GMPP), leading to improved power extraction, reduced tracking time, and enhanced system stability. The findings highlight the suitability of the developed GWEO-based MPPT technique for real-time PV applications exposed to variable environmental conditions.
Keywords
Grey Wolf Equilibrium Optimization (GWEO), Particle Swarm Optimization (PSO), Global maximum power point (GMPP), Grey wolf Optimization (GWO), MPPT.
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