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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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2015
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| 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 |
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| Summary: | 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. |
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