Comparative analysis of GWO MPPT with conventional techniques in shaded PV arrays
Lyu Guanghua, Deedar Ali Jamro, Abdul Qadir Rahimoon, Danish Asad Memon, Zubeda Bhatti, Syed Hadi Hussain Shah
Abstract
Partial shading conditions (PSC) introduce multiple peaks in the power–voltage (P–V) curve of photovoltaic (PV) systems, leading conventional maximum power point tracking (MPPT) techniques to become trapped in local maxima. This limits their ability to extract the global maximum power point (GMPP), resulting in significant power loss. Traditional algorithms such as Perturb and Observe (P&O) and Incremental Conductance (INC) typically fail under such conditions, especially during dynamic irradiance variations. This paper presents a comparative analysis of the Grey Wolf Optimizer (GWO)-based MPPT algorithm under realistic shading conditions. A detailed simulation framework was developed in MATLAB/Simulink, incorporating series-connected PV modules subjected to two distinct partial shading patterns. Performance evaluation focused on MPPT efficiency, convergence time, and steady-state power oscillation. Simulation results demonstrate that the GWO algorithm consistently tracks the GMPP with an average efficiency of 98.15%, outperforming P&O (54%) and INC (74%). It also achieves a faster convergence time of 0.0603 seconds and maintains output power oscillations below 2 watts. Additionally, GWO adapts more effectively to sudden irradiance changes, preserving maximum power delivery even under unstable environmental conditions. These results confirm the superior tracking capability, speed, and robustness of the GWO-based approach, establishing it as a practical and effective MPPT solution for PV systems exposed to partial shading.