Implementation and Performance Analysis of Optimization based GMPP Tracking Algorithms for a PV Array under Various Shading Effects

The efficiency of photovoltaic (PV) systems is largely affected under partial shading conditions (PSCs), which create multiple maximum power peaks while tracking output power. To address this challenge, this paper introduces an adapted grey-wolf optimization (AGO) algorithm for efficient power extraction from a PV system under various PSCs without requiring any sensing components. It utilizes simplified computational blocks and a constant value for the convergence factor to explicit the convergence towards global maximum power point (GMPP). The proposed GMPP tracking algorithm is implemented in MATLAB/Simulink and validated through comparative study with a fast converging technique such as APO-MPC. Results confirm that the proposed approach offers higher tracking speed and faster convergence toward the GMPP.