An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time

Mirhassani, S.M. and Golroodbari, S.Z.M and Goiroodbari, S.M.M. and Mekhilef, Saad (2015) An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time. International Journal of Electrical Power & Energy Systems, 64. pp. 761-770. ISSN 0142-0615, DOI https://doi.org/10.1016/j.ijepes.2014.07.074.

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Abstract

This paper presents an improved maximum power point tracking (MPPT) strategy for photovoltaic (PV) systems based on particle swarm optimization (PSO). The capability of the PSO algorithm to cope with partially shaded conditions (PSCs) is the primary motivation of this research. Unlike conventional PSO-based MPPT systems, a variable sampling time strategy (VSTS) based on the investigation of the dynamic behavior of converter current is deployed to increase system tracking time. The performance of the proposed system is evaluated using MATLAB simulation and experimentation, in which a digital signal controller is used to implement the proposed algorithm on a real boost converter connected to a PV simulator. The main advantage of the proposed algorithm is fast and accurate performance under different conditions, including PSCs. (C) 2014 Elsevier Ltd. All rights reserved.

Item Type: Article
Funders: Ministry of Higher Education of Malaysia University of Malaya UM.C/HIR/MOHE/ENG/D000024
Additional Information: As7od Times Cited:0 Cited References Count:28
Uncontrolled Keywords: Maximum power point tracking, particle swarm optimization, partially shaded condition, variable sampling time, incremental conductance mppt, photovoltaic systems, fuzzy controller, pv, stabilization, converter, implementation, algorithm, network, delays,
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 04 Aug 2015 02:12
Last Modified: 25 Oct 2019 04:21
URI: http://eprints.um.edu.my/id/eprint/13853

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