PV Output Power Enhancement using Meta-Heuristic Crow Search Algorithm under Uniform and Shading Condition

Abstract

In uniform conditions, the power-voltage (P_V) curve has a unique global peak irradiance and no local peak irradiance. But in non-uniform or shading conditions P_V curve has many local peaks with a unique global peak. Therefore, tracking the global peak is the key factor to improve the photo voltaic (PV) performance under uniform and shading conditions. To track global peak radiation, maximum power point tracking (MPPT) controller is a mandatory requirement. Numerous soft computing algorithms are developed and explained in past decades. But the ability to track the global maximum peak (GMP) is not assured under shading conditions due to trapping with local peaks instead of global peaks. In this research article, a new meta–heuristic crow search algorithm (CSA) is developed and extracted GMP under uniform and shading conditions of the PV module. The highlight of CSA is it works on dual mode search ability namely intensification and diversification. Because of this dual-mode operation, the local peak convergence problem is solved and it tracks GMP very fast. The experimental outcomes show that the CSA technique provides higher efficiency and faster tracking time