JAYA Algorithm Based on Levy Flight for Global MPPT Under Partial Shading in Photovoltaic System

Recent technologies associated with solar photovoltaic (PV) systems tend to depend mostly on irradiance. In a PV array, the distribution of irradiance is unequal varying from module to module under partial shading (PS) conditions. Because of the PS of the PV array; the number of peaks in power-voltage (P-V) characteristics increases. In such cases, it would be difficult to track the highest peak or global peak (GP) point of P-V curve using traditional maximum power point tracking (MPPT) algorithms, such as perturb and observe (P&O), hill climbing (HC), and incremental conductance (INC). However, these work effectively only under constant irradiance conditions, i.e., to track single peak P-V curves. However, in order to track the GP point of P-V curves, the conventional JAYA algorithm is used, but it takes more tracking oscillations and convergence time due to fewer control parameters. To overcome the drawbacks of the JAYA algorithm, this article proposes a JAYA algorithm based on the Levy flight (JAYA-LF) under static and dynamic conditions of PV array. The performance of the proposed algorithm is examined through MATLAB/SIMULINK and from experiments with the designed prototype. The results observed by the proposed algorithm are then compared with conventional JAYA and particle swarm optimization (PSO) algorithm to show the superiority and better performance of the algorithm that combines JAYA with Levy flight.

Automated summary

This article proposes a JAYA algorithm based on the Levy flight for improving power tracking efficiency in solar photovoltaic arrays under static and dynamic conditions. The performance of the algorithm is examined through MATLAB/SIMULINK and experiments with a designed prototype, showing superior results compared to conventional JAYA and particle swarm optimization algorithms.