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...
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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 |
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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 |
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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 |
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2015 |
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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 |
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13.18916 |