Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions


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.

Publication DOI:
Divisions: College of Engineering & Physical Sciences
Additional Information: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( 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
Publication ISSN: 1996-1073
Last Modified: 08 Dec 2023 11:00
Date Deposited: 20 Feb 2019 16:06
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Related URLs: https://www.mdp ... 6-1073/12/4/623 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-02-15
Accepted Date: 2019-02-13
Authors: Alshareef, Muhannad
Lin, Zhengyu (ORCID Profile 0000-0001-7733-2431)
Ma, Mingyao
Cao, Wenping (ORCID Profile 0000-0002-8133-3020)



Version: Published Version

License: Creative Commons Attribution

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