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http://dx.doi.org/10.6113/JPE.2018.18.6.1805

Humpback Whale Assisted Hybrid Maximum Power Point Tracking Algorithm for Partially Shaded Solar Photovoltaic Systems  

Premkumar, Manoharan (Department of Electrical and Electronics Engineering, GMR Institute of Technology)
Sumithira, Rameshkumar (Department of Electrical and Electronics Engineering, Government College of Engineering)
Publication Information
Journal of Power Electronics / v.18, no.6, 2018 , pp. 1805-1818 More about this Journal
Abstract
This paper proposes a novel hybrid maximum power point tracking (MPPT) algorithm combining a Whale Optimization Algorithm (WOA) and the conventional Perturb & Observation (P&O) to track/extract the highest amount of power from a solar photovoltaic (SPV) system working under partial shading conditions (PSCs). The proposed hybrid algorithm is based on a WOA which predicts the initial global peak (GP) and is followed by P&O in the final stage to achieve a quicker convergence to a GP. Thus, this hybrid algorithm overcomes the computational burden encountered in a standalone WOA, grey wolf optimization (GWO) and hybrid GWO reported in the literature. The conventional algorithm searches for the maximum power point (MPP) in the predicted region by the WOA. The proposed MPPT technique is modelled and simulated using MATLAB/Simulink for simulating an environment to check its effectiveness in accurately tracking the MPP during the GP region. This hybrid algorithm is compared with a standalone WOA, GWO and hybrid GWO. From the simulating results, it is shown that the proposed algorithm offers high tracking performance and that it increases the output power level of a SPV system under partial shading. The algorithm also verified experimentally on various PSCs.
Keywords
GWO; Hybrid GWO; Hybrid WOA; P&O; Partial shading; WOA;
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