Cuckoo Search Algorithms for Maximum Power Point Intelligent Tracking of PV Array Under Partial Shading Conditions

Photovoltaic array (PV) always works with less than 20% efficiency and never reaches the maximum power due to changes in temperature, radiation, partial shading, and others. The PV has a power and voltage characteristic curve with multiple peaks for the above reason. In these cases, using traditional methods to find the highest power point would not be reliable. It leads to a decrease in the efficiency of the PV. Therefore, researchers prefer other methods to solve this problem. One of the ways is to use modern techniques that depend on algorithms to track the highest energy point in the PV. This study suggests the cuckoo search algorithm (CSA) to find the maximum power point (MPP) in the PV panels and then compare the results with the traditional method of perturbation and observation (P&O). MATLAB/Simulink was used as an environment to simulate the four patterns representing different cases of partial shading. The results found that the CSA can track MPP with high accuracy. It may reach an average efficiency higher than 99.7% with tracking time between (0.17–0.23) s under different partial shading conditions. The results were compared with the P&O method, which showed its superiority in tracking accuracy, tracking speed, peak power, tracking power, and tracking efficiency for MPP.