Work

Revolutionizing photovoltaic power: An enhanced Grey Wolf Optimizer for ultra-efficient MPPT under partial shading conditions

Year: 2025

Type: article

Abstract: This paper presents an Enhanced Grey Wolf Optimizer (E-GWO) algorithm for Maximum Power Point Tracking (MPPT) in photovoltaic (PV) systems under partial shading conditions. The proposed E-GWO introduces a novel parameter minimization strategy for the convergence factor ω , enabling rapid and precise tracking of the global maximum power point (GMPP) without overshoot. Key improvements to the standard GWO framework enhance tracking accuracy, stability, and overall system performance . The proposed MPPT approach is validated through extensive simulations and real-world experiments implemented on a dual-core DSP LAUNCHXL-F28379D using MATLAB/Simulink. Experimental results demonstrate that E-GWO reduces tracking time by up to 99.90% compared to traditional GWO methods while increasing dynamic tracking efficiency by over 9%. Furthermore, the E-GWO consistently outperforms conventional GWO variants and other swarm-based algorithms, ensuring superior power output in diverse shading scenarios.

Source: Scientific African

DOI: 10.1016/j.sciaf.2025.e02586

Authors: Hajar Ahessab, Ahmed Gaga, Benachir EL Hadadi

Institution: Université Sultan Moulay Slimane

Language: English

Topic: Photovoltaic System Optimization Techniques

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $590