Fast Convergence Modified Cuckoo Search Algorithm to Pursue String PV Modules Maximum Power Point under Partial Shading Conditions

Photovoltaic modules under partially shaded conditions have complicated power-against-voltage characteristics curve with numerous power peaks comprising of global power peak and local power peaks. In order to achieve the utmost benefits, the Photovoltaic system should be forced to operate at the global maximum power point (GMPP) and that's what the conventional methods have failed to achieve. Many soft computing techniques have been designed to track (GMPP) but, the main challenge is how to achieve that tracking with the fastest time, the lowest fluctuations, minimal tuning parameters, and the highest efficiency. In this paper, a modified cuckoo search algorithm is proposed after investigating the main idea of the cuckoo search algorithm and how it was applied to solve the problem of numerous power peaks. This modified algorithm has the ability to exclude or promote some parts of the solution search space and redirects the newly generated random sample towards the promoted space. Further, the proposed algorithm has been simulated for a patterns' power-voltage curve by using MATLAB/Simulink software. The simulation results indicate that the proposed method outperforms the conventional cuckoo search algorithm in terms of the global maximum power point tracking (GMPPT) speed with the lowest fluctuations and highest efficiency.