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

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dc.citedby69
dc.contributor.authorYousri D.en_US
dc.contributor.authorBabu T.S.en_US
dc.contributor.authorAllam D.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorEtiba M.B.en_US
dc.contributor.authorid56688582500en_US
dc.contributor.authorid56267551500en_US
dc.contributor.authorid55940454800en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid57211810532en_US
dc.date.accessioned2023-05-29T07:28:47Z
dc.date.available2023-05-29T07:28:47Z
dc.date.issued2019
dc.descriptionGlobal optimization; Photovoltaic cells; Algorithm parameters; Environmental conditions; Environmental phenomena; Global maximum power point tracking; Maximum power point tracking techniques; Optimization algorithms; Photovoltaic systems; Standard versions; Maximum power point trackersen_US
dc.description.abstractA 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.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ACCESS.2019.2937600
dc.identifier.epage121445
dc.identifier.scopus2-s2.0-85075066599
dc.identifier.spage121432
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075066599&doi=10.1109%2fACCESS.2019.2937600&partnerID=40&md5=c5571914453d9f00fd44ab30fab89740
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24916
dc.identifier.volume7
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.titleA novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditionsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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