A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions

A partial shading condition is an environmental phenomenon that causes multiple peaks in Photovoltaic (PV) characteristics. Introducing robust and reliable Maximum Power Point Tracking technique is essential in PV systems to extract the Global Maximum Power Point (GMPP) irrespective of the environme...

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Main Authors: Yousri, D., Babu, T.S., Allam, D., Ramachandaramurthy, V.K., Etiba, M.B.
Format: Article
Language:English
Published: 2020
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spelling my.uniten.dspace-132752020-07-03T08:04:23Z A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions Yousri, D. Babu, T.S. Allam, D. Ramachandaramurthy, V.K. Etiba, M.B. A partial shading condition is an environmental phenomenon that causes multiple peaks in Photovoltaic (PV) characteristics. Introducing robust and reliable Maximum Power Point Tracking technique is essential in PV systems to extract the Global Maximum Power Point (GMPP) irrespective of the environmental conditions. Therefore in this manuscript, a novel optimization algorithm is implemented for MPPT. The developed technique named Chaotic Flower Pollination Algorithm (C-FPA) merges the chaos maps (Logistic, sine, and tent maps) to tune the basic algorithm parameters adaptively. The effectiveness of the introduced variants is proved using several patterns of partial shading condition. Moreover, these variants are certified for tracking the GMPP in case of dynamic and sudden variation in the irradiance conditions. Several statistical analysis is carried out to evaluate the performance of the proposed variants in comparison with the standard version of the Flower Pollination Algorithm (FPA). The significant outcome clarifies that combining the chaos maps with FPA improves the dependability and stability of the FPA and offers higher tracking efficiency with a reduction of tracking time by 50% when compared to FPA. Moreover, the proposed C-FPA provides a better dynamic response, especially with the tent chaos map. © 2019 Institute of Electrical and Electronics Engineers Inc. All rights reserved. 2020-02-03T03:31:29Z 2020-02-03T03:31:29Z 2019 Article 10.1109/ACCESS.2019.2937600 en
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description A partial shading condition is an environmental phenomenon that causes multiple peaks in Photovoltaic (PV) characteristics. Introducing robust and reliable Maximum Power Point Tracking technique is essential in PV systems to extract the Global Maximum Power Point (GMPP) irrespective of the environmental conditions. Therefore in this manuscript, a novel optimization algorithm is implemented for MPPT. The developed technique named Chaotic Flower Pollination Algorithm (C-FPA) merges the chaos maps (Logistic, sine, and tent maps) to tune the basic algorithm parameters adaptively. The effectiveness of the introduced variants is proved using several patterns of partial shading condition. Moreover, these variants are certified for tracking the GMPP in case of dynamic and sudden variation in the irradiance conditions. Several statistical analysis is carried out to evaluate the performance of the proposed variants in comparison with the standard version of the Flower Pollination Algorithm (FPA). The significant outcome clarifies that combining the chaos maps with FPA improves the dependability and stability of the FPA and offers higher tracking efficiency with a reduction of tracking time by 50% when compared to FPA. Moreover, the proposed C-FPA provides a better dynamic response, especially with the tent chaos map. © 2019 Institute of Electrical and Electronics Engineers Inc. All rights reserved.
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author Yousri, D.
Babu, T.S.
Allam, D.
Ramachandaramurthy, V.K.
Etiba, M.B.
spellingShingle Yousri, D.
Babu, T.S.
Allam, D.
Ramachandaramurthy, V.K.
Etiba, M.B.
A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
author_facet Yousri, D.
Babu, T.S.
Allam, D.
Ramachandaramurthy, V.K.
Etiba, M.B.
author_sort Yousri, D.
title A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
title_short A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
title_full A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
title_fullStr A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
title_full_unstemmed A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
title_sort novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
publishDate 2020
_version_ 1672614219612160000
score 13.222552