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A Robust Strategy Based on Marine Predators Algorithm for Large Scale Photovoltaic Array Reconfiguration to Mitigate the Partial Shading Effect on the Performance of PV System

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dc.citedby93
dc.contributor.authorYousri D.en_US
dc.contributor.authorBabu T.S.en_US
dc.contributor.authorBeshr E.en_US
dc.contributor.authorEteiba M.B.en_US
dc.contributor.authorAllam D.en_US
dc.contributor.authorid56688582500en_US
dc.contributor.authorid56267551500en_US
dc.contributor.authorid16201948000en_US
dc.contributor.authorid6603527538en_US
dc.contributor.authorid55940454800en_US
dc.date.accessioned2023-05-29T08:13:00Z
dc.date.available2023-05-29T08:13:00Z
dc.date.issued2020
dc.descriptionParticle swarm optimization (PSO); Photovoltaic effects; Solar power generation; Algorithm performance; Comprehensive comparisons; Partial shading effects; Particle swarm optimizers; Photovoltaic arrays; Population-based algorithm; Weighted objective function; Wilcoxon signed rank test; Photovoltaic cellsen_US
dc.description.abstractLarge-scale solar photovoltaic (PV) plants play an essential role in providing the increasing demand for energy in recent time. Therefore, in the purpose of achieving the highest harvested power under the partial shading conditions as well as protecting the PV array from the hot-spot calamity, the PV reconfiguration strategy is established as an efficient procedure. This is performed by redistribution of PV modules according to their levels of shading. Motivated by this, the authors in this article have introduced a novel population-based algorithm that is known as marine predators algorithm (MPA) to restructure the PV array dynamically. Moreover, a novel objective function is introduced to enhance the algorithm performance rather than utilizing the regular weighted objective function in the literature. The effectiveness of the proposed algorithms based on the novel objective function is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the obtained results are compared with a regular total-cross-tied (TCT) connection, manta ray foraging optimization (MRFO), harris hawk optimizer (HHO) and particle swarm optimizer (PSO) based reconfiguration techniques. Furthermore, to demonstrate the suitability of the proposed methods, large scale PV arrays of 16�16 and 25�25 are considered and evaluated. The results reveal that MPA enhanced the PV array power by percentage of 28.6 %, 2.7 % and 5.7 % in cases of 9�9 , 16�16 and 25�25 PV arrays, respectively. The comprehensive comparisons endorse that MPA shows a successful shade dispersion; hence the number of multiple peaks in the PV characteristics has reduced, and high values of power have been harvested with least mean execution time in comparison with PSO, HHO and MRFO. Moreover, the Wilcoxon signed-rank test has been accomplished to confirm the reliability and applicability of the proposed approach for the PV large scale arrays as well. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9109577
dc.identifier.doi10.1109/ACCESS.2020.3000420
dc.identifier.epage112426
dc.identifier.scopus2-s2.0-85087640803
dc.identifier.spage112407
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85087640803&doi=10.1109%2fACCESS.2020.3000420&partnerID=40&md5=c3921c7099896140650e79229bb43725
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25702
dc.identifier.volume8
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.titleA Robust Strategy Based on Marine Predators Algorithm for Large Scale Photovoltaic Array Reconfiguration to Mitigate the Partial Shading Effect on the Performance of PV Systemen_US
dc.typeArticleen_US
dspace.entity.typePublication
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