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...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
2020
|
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uniten.dspace-13275 |
---|---|
record_format |
dspace |
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. |
format |
Article |
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 |