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Accelerated particle swarm optimization for photovoltaic maximum power point tracking under partial shading conditions

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posted on 2019-07-04, 13:04 authored by Muhannad Alshareef, Zhengyu LinZhengyu Lin, Mingyao Ma, Wenping Cao
© 2019 by the authors. This paper presents an accelerated particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to track global maximum power point (MPP) of photovoltaic (PV) generation under partial shading conditions. Conventional PSO-based MPPT algorithms have common weaknesses of a long convergence time to reach the global MPP and oscillations during the searching. The proposed algorithm includes a standard PSO and a perturb-and-observe algorithm as the accelerator. It has been experimentally tested and compared with conventional MPPT algorithms. Experimental results show that the proposed MPPT method is effective in terms of high reliability, fast dynamic response, and high accuracy in tracking the global MPP.

Funding

This research has received scholarship from Saudi Arabia Cultural Bureau in the UK and funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 734796.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Energies

Volume

12

Issue

4

Citation

ALSHAREEF, M. ... et al., 2019. Accelerated particle swarm optimization for photovoltaic maximum power point tracking under partial shading conditions. Energies, 12(4): 623.

Publisher

© the authors. Published by MDPI

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

2019-02-13

Publication date

2019-02-15

Notes

This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

eISSN

1996-1073

Language

  • en

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