Please use this identifier to cite or link to this item: http://dlib.scu.ac.ir/handle/Hannan/298261
Title: A biological swarm chasing algorithm for tracking the PV maximum power point
Authors: Chen, Liang Rui;Tsai, Chih Hui;Lin, Yuan Li;Lai, Yen Shin
subject: Maximum power point tracking (MPPT);Particle swarm optimization;Photovoltaic (PV);Swarm intelligence;10.1109/TEC.2009.2038067
Year: 2010
Publisher: Ieee
Abstract: In this paper, a novel photovoltaic (PV) maximum power point tracking (MPPT) based on biological swarm chasing behavior is proposed to increase the MPPT performance for a module-integrated PV power system. Each PV module is viewed as a particle, and as a result, the maximum power point is viewed as the moving target. Thus, every PV module can chase the maximum power point (MPP) automatically. A 525 W prototype constructed by three parallel-connected 175 W PV modules is implemented to assess the MPPT performance. Comparing with a typical perturb and observe (P & O) MPPT method, the MPPT efficiency ÂMPPT is improved about 12.19% in transient state by the proposed MPPT as theoretical prediction.
Description: 
URI: http://localhost/handle/Hannan/298261
ISSN: 0885-8969
More Information: VOLUME : 25 ISSUE : 2 START PAGE : 484 END PAGES : 493
Appears in Collections:2010

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Title: A biological swarm chasing algorithm for tracking the PV maximum power point
Authors: Chen, Liang Rui;Tsai, Chih Hui;Lin, Yuan Li;Lai, Yen Shin
subject: Maximum power point tracking (MPPT);Particle swarm optimization;Photovoltaic (PV);Swarm intelligence;10.1109/TEC.2009.2038067
Year: 2010
Publisher: Ieee
Abstract: In this paper, a novel photovoltaic (PV) maximum power point tracking (MPPT) based on biological swarm chasing behavior is proposed to increase the MPPT performance for a module-integrated PV power system. Each PV module is viewed as a particle, and as a result, the maximum power point is viewed as the moving target. Thus, every PV module can chase the maximum power point (MPP) automatically. A 525 W prototype constructed by three parallel-connected 175 W PV modules is implemented to assess the MPPT performance. Comparing with a typical perturb and observe (P & O) MPPT method, the MPPT efficiency ÂMPPT is improved about 12.19% in transient state by the proposed MPPT as theoretical prediction.
Description: 
URI: http://localhost/handle/Hannan/298261
ISSN: 0885-8969
More Information: VOLUME : 25 ISSUE : 2 START PAGE : 484 END PAGES : 493
Appears in Collections:2010

Files in This Item:
File Description SizeFormat 
AL1745632.pdf1.32 MBAdobe PDFThumbnail
Preview File
Title: A biological swarm chasing algorithm for tracking the PV maximum power point
Authors: Chen, Liang Rui;Tsai, Chih Hui;Lin, Yuan Li;Lai, Yen Shin
subject: Maximum power point tracking (MPPT);Particle swarm optimization;Photovoltaic (PV);Swarm intelligence;10.1109/TEC.2009.2038067
Year: 2010
Publisher: Ieee
Abstract: In this paper, a novel photovoltaic (PV) maximum power point tracking (MPPT) based on biological swarm chasing behavior is proposed to increase the MPPT performance for a module-integrated PV power system. Each PV module is viewed as a particle, and as a result, the maximum power point is viewed as the moving target. Thus, every PV module can chase the maximum power point (MPP) automatically. A 525 W prototype constructed by three parallel-connected 175 W PV modules is implemented to assess the MPPT performance. Comparing with a typical perturb and observe (P & O) MPPT method, the MPPT efficiency ÂMPPT is improved about 12.19% in transient state by the proposed MPPT as theoretical prediction.
Description: 
URI: http://localhost/handle/Hannan/298261
ISSN: 0885-8969
More Information: VOLUME : 25 ISSUE : 2 START PAGE : 484 END PAGES : 493
Appears in Collections:2010

Files in This Item:
File Description SizeFormat 
AL1745632.pdf1.32 MBAdobe PDFThumbnail
Preview File