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A new metaphor-less algorithms for the photovoltaic cell parameter estimation

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dc.citedby70
dc.contributor.authorPremkumar M.en_US
dc.contributor.authorBabu T.S.en_US
dc.contributor.authorUmashankar S.en_US
dc.contributor.authorSowmya R.en_US
dc.contributor.authorid57191413142en_US
dc.contributor.authorid56267551500en_US
dc.contributor.authorid57199091461en_US
dc.contributor.authorid57219263030en_US
dc.date.accessioned2023-05-29T08:10:31Z
dc.date.available2023-05-29T08:10:31Z
dc.date.issued2020
dc.descriptionMultiobjective optimization; Parameter estimation; Photoelectrochemical cells; Photovoltaic cells; Solar power generation; Cell parameter; Estimated parameter; Local minimums; Optimization algorithms; Pre-mature convergences; Solar cell parameters; Solar photovoltaic system; Solar PVs; Solar cellsen_US
dc.description.abstractThe performance of the solar photovoltaic (PV) system can be improved by an accurate modelling of the solar cells, but cell modelling is inaccurate due to the lack of precise solar cell parameters. To model a reliable solar PV cell, the required parameters will not be provided in the manufacturer's datasheet. Therefore, it's necessary to estimate the required parameters adequately. Thereby, with this observation, in this paper, proposed a simple multi-objective optimization algorithm to estimate the cell parameters. Various optimization algorithms address this issue; however, most of the algorithms produce suboptimal results due to local minima and premature convergence. So, this paper proposes two simple metaphor-less algorithms named as Rao-2 (R-II), and Rao-3 (R-III) algorithm to estimate the PV cell parameters. The performance of the proposed algorithms is compared with other well-known optimization algorithms to show the proficiency of the proposed algorithms. To validate the performance of the proposed algorithms, the estimated parameters are compared with experimental results, including statistical analysis. Moreover, from the results, it can be judged that the proposed algorithms are more suitable for the estimation of three types of solar PV models effectively. � 2020 Elsevier GmbHen_US
dc.description.natureFinalen_US
dc.identifier.ArtNo164559
dc.identifier.doi10.1016/j.ijleo.2020.164559
dc.identifier.scopus2-s2.0-85081653751
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85081653751&doi=10.1016%2fj.ijleo.2020.164559&partnerID=40&md5=a5bdfc8fa7bc9e1a1b32c1184fe8d412
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25530
dc.identifier.volume208
dc.publisherElsevier GmbHen_US
dc.sourceScopus
dc.sourcetitleOptik
dc.titleA new metaphor-less algorithms for the photovoltaic cell parameter estimationen_US
dc.typeArticleen_US
dspace.entity.typePublication
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