Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3695
Title: JAYA Algorithm Based on Lévy Flight for Global MPPT under Partial Shading in Photovoltaic System
Authors: Motamarri, Rambabu
Bhookya, Nagu
Keywords: Particle swarm optimization (PSO)
Photovoltaic cells
Issue Date: 2021
Publisher: IEEE Journal of Emerging and Selected Topics in Power Electronics
Citation: 10.1109/JESTPE.2020.3036405
Abstract: Recent technologies associated with solar photo voltaic (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 Lévy 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.
Description: NITW
URI: http://localhost:8080/xmlui/handle/123456789/3695
Appears in Collections:Electrical Engineering

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