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

Multiobjective 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 cells

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Bibliographic Details
Main Authors: Premkumar M., Babu T.S., Umashankar S., Sowmya R.
Other Authors: 57191413142
Format: Article
Published: Elsevier GmbH 2023
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spelling my.uniten.dspace-255302023-05-29T16:10:31Z A new metaphor-less algorithms for the photovoltaic cell parameter estimation Premkumar M. Babu T.S. Umashankar S. Sowmya R. 57191413142 56267551500 57199091461 57219263030 Multiobjective 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 cells The 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 GmbH Final 2023-05-29T08:10:31Z 2023-05-29T08:10:31Z 2020 Article 10.1016/j.ijleo.2020.164559 2-s2.0-85081653751 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081653751&doi=10.1016%2fj.ijleo.2020.164559&partnerID=40&md5=a5bdfc8fa7bc9e1a1b32c1184fe8d412 https://irepository.uniten.edu.my/handle/123456789/25530 208 164559 Elsevier GmbH Scopus
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/
description Multiobjective 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 cells
author2 57191413142
author_facet 57191413142
Premkumar M.
Babu T.S.
Umashankar S.
Sowmya R.
format Article
author Premkumar M.
Babu T.S.
Umashankar S.
Sowmya R.
spellingShingle Premkumar M.
Babu T.S.
Umashankar S.
Sowmya R.
A new metaphor-less algorithms for the photovoltaic cell parameter estimation
author_sort Premkumar M.
title A new metaphor-less algorithms for the photovoltaic cell parameter estimation
title_short A new metaphor-less algorithms for the photovoltaic cell parameter estimation
title_full A new metaphor-less algorithms for the photovoltaic cell parameter estimation
title_fullStr A new metaphor-less algorithms for the photovoltaic cell parameter estimation
title_full_unstemmed A new metaphor-less algorithms for the photovoltaic cell parameter estimation
title_sort new metaphor-less algorithms for the photovoltaic cell parameter estimation
publisher Elsevier GmbH
publishDate 2023
_version_ 1806425738997399552
score 13.222552

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