Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition

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dc.authoridCikan, Murat/0000-0001-6723-5769
dc.authoridTumay, Mehmet/0000-0002-6055-3761
dc.authoridAygul, Kemal/0000-0002-7840-5441
dc.authoridDemirdelen, Tugce/0000-0002-1602-7262
dc.contributor.authorAygul, Kemal
dc.contributor.authorCikan, Murat
dc.contributor.authorDemirdelen, Tugce
dc.contributor.authorTumay, Mehmet
dc.date.accessioned2025-01-06T17:43:52Z
dc.date.available2025-01-06T17:43:52Z
dc.date.issued2023
dc.description.abstractBecause of dust, trees, high buildings in the surrounding area, partial shading conditions (PSC) occur in photovoltaic (PV) systems. This condition affects the power output of the PV system. Under PSC there is a global maximum power point (GMPP) besides there are a few local maximum power points (LMPP). This condition makes the maximum power point tracking (MPPT) procedure a challenging task. In order to solve this issue, soft computing techniques such as gray wolf optimization (GWO), particle swarm optimization (PSO) and Gravitational Search Algorithm (GSA) are implemented. However, the performance of MPP trackers still needs to be improved. The main contribution of this paper is improving the tracking speed by implementing BOA to the MPPT of the PV system under PSC. Thus, in real-time applications a promising alternative presented to the literature to improve the performance of the PV systems under variable PSC because of its fast tracking speed. PV system consists of PV array, boost converter and load are modeled and simulated in MATLAB/Simulink. BOA algorithm is implemented for three different insolation scenarios on the PV array. The results of the BOA algorithm verified by a comparative analysis with PSO-GSA and GWO algorithms. The results show that BOA can give high accuracy and better tracking speed than these algorithms in recent literature.
dc.description.sponsorshipResearch Fund of Cukurova University [:10587]
dc.description.sponsorshipThis work was supported by Research Fund of Cukurova University. Project Number:10587
dc.identifier.doi10.1080/15567036.2019.1677818
dc.identifier.endpage8355
dc.identifier.issn1556-7036
dc.identifier.issn1556-7230
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85074364712
dc.identifier.scopusqualityQ1
dc.identifier.startpage8337
dc.identifier.urihttps://doi.org/10.1080/15567036.2019.1677818
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2844
dc.identifier.volume45
dc.identifier.wosWOS:000490354400001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Inc
dc.relation.ispartofEnergy Sources Part A-Recovery Utilization and Environmental Effects
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectPartial shading
dc.subjectphotovoltaic
dc.subjectsolar
dc.subjectenergy
dc.subjectbutterfly optimization algorithm
dc.subjectMPPT
dc.titleButterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition
dc.typeArticle

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