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

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 P...

Full description

Saved in:
Bibliographic Details
Main Authors: Mirhassani, S.M., Golroodbari, S.Z.M, Goiroodbari, S.M.M., Mekhilef, Saad
Format: Article
Language:English
Published: 2015
Subjects:
Online Access:http://eprints.um.edu.my/13853/1/An_improved_particle_swarm_optimization_based.pdf
http://eprints.um.edu.my/13853/
http://www.sciencedirect.com/science/article/pii/S0142061514005183
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.um.eprints.13853
record_format eprints
spelling my.um.eprints.138532019-10-25T04:21:03Z http://eprints.um.edu.my/13853/ An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time Mirhassani, S.M. Golroodbari, S.Z.M Goiroodbari, S.M.M. Mekhilef, Saad T Technology (General) TK Electrical engineering. Electronics Nuclear engineering 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. 2015-01 Article PeerReviewed application/pdf en http://eprints.um.edu.my/13853/1/An_improved_particle_swarm_optimization_based.pdf 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 http://www.sciencedirect.com/science/article/pii/S0142061514005183 DOI 10.1016/j.ijepes.2014.07.074
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Mirhassani, S.M.
Golroodbari, S.Z.M
Goiroodbari, S.M.M.
Mekhilef, Saad
An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
description 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.
format Article
author Mirhassani, S.M.
Golroodbari, S.Z.M
Goiroodbari, S.M.M.
Mekhilef, Saad
author_facet Mirhassani, S.M.
Golroodbari, S.Z.M
Goiroodbari, S.M.M.
Mekhilef, Saad
author_sort Mirhassani, S.M.
title An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
title_short An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
title_full An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
title_fullStr An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
title_full_unstemmed An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
title_sort improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
publishDate 2015
url http://eprints.um.edu.my/13853/1/An_improved_particle_swarm_optimization_based.pdf
http://eprints.um.edu.my/13853/
http://www.sciencedirect.com/science/article/pii/S0142061514005183
_version_ 1648736130413101056
score 13.18916