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A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules
Parameters extraction is instrumental to standard PV cells design. Reports indicates that heuristic algorithms are the most effective methods for accurately determinining the values of parameters. However, local concentration is against recent heuristic methods, and they are inhibited producing opti...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045010/ https://www.ncbi.nlm.nih.gov/pubmed/33869869 http://dx.doi.org/10.1016/j.heliyon.2021.e06673 |
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author | Gnetchejo, Patrick Juvet Ndjakomo Essiane, Salomé Dadjé, Abdouramani Ele, Pierre |
author_facet | Gnetchejo, Patrick Juvet Ndjakomo Essiane, Salomé Dadjé, Abdouramani Ele, Pierre |
author_sort | Gnetchejo, Patrick Juvet |
collection | PubMed |
description | Parameters extraction is instrumental to standard PV cells design. Reports indicates that heuristic algorithms are the most effective methods for accurately determinining the values of parameters. However, local concentration is against recent heuristic methods, and they are inhibited producing optimal results. This paper seeks to show that combining the heuristics algorithms with the Newton Raphson method can considerably increased the accuracy of results. An inspired artifact technique from the drone squadron simulation from control center is proposed for the extraction of the best constitutive parameters. This study equally provides clarifications on the approaches recently reported and proposed to build objective function. Furthermore, comparative evaluation of the current ten best heuristics algorithms that are published in the PV estimation domain is also undertaken. Moreover, this study investigates the convergence of algorithms when points of the number of current-voltage characteristics are varied. The results from this study highlight the differences between the two formulation, and it shows the best formulation accuracy. The results obtained from seven study cases that are considered in this present study, with the combined Newton Raphson performance method and Drone Squadron optimisation, were employed to extract precise PV module parameters.The study of the numbers of points reveals that the algorithm converges and is more precise when the numbers of points of the I-V characteristic are reduced. However, if these points are minimal, the algorithm will be hindered from returning optimal results. |
format | Online Article Text |
id | pubmed-8045010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-80450102021-04-16 A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules Gnetchejo, Patrick Juvet Ndjakomo Essiane, Salomé Dadjé, Abdouramani Ele, Pierre Heliyon Research Article Parameters extraction is instrumental to standard PV cells design. Reports indicates that heuristic algorithms are the most effective methods for accurately determinining the values of parameters. However, local concentration is against recent heuristic methods, and they are inhibited producing optimal results. This paper seeks to show that combining the heuristics algorithms with the Newton Raphson method can considerably increased the accuracy of results. An inspired artifact technique from the drone squadron simulation from control center is proposed for the extraction of the best constitutive parameters. This study equally provides clarifications on the approaches recently reported and proposed to build objective function. Furthermore, comparative evaluation of the current ten best heuristics algorithms that are published in the PV estimation domain is also undertaken. Moreover, this study investigates the convergence of algorithms when points of the number of current-voltage characteristics are varied. The results from this study highlight the differences between the two formulation, and it shows the best formulation accuracy. The results obtained from seven study cases that are considered in this present study, with the combined Newton Raphson performance method and Drone Squadron optimisation, were employed to extract precise PV module parameters.The study of the numbers of points reveals that the algorithm converges and is more precise when the numbers of points of the I-V characteristic are reduced. However, if these points are minimal, the algorithm will be hindered from returning optimal results. Elsevier 2021-04-08 /pmc/articles/PMC8045010/ /pubmed/33869869 http://dx.doi.org/10.1016/j.heliyon.2021.e06673 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Gnetchejo, Patrick Juvet Ndjakomo Essiane, Salomé Dadjé, Abdouramani Ele, Pierre A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules |
title | A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules |
title_full | A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules |
title_fullStr | A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules |
title_full_unstemmed | A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules |
title_short | A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules |
title_sort | combination of newton-raphson method and heuristics algorithms for parameter estimation in photovoltaic modules |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045010/ https://www.ncbi.nlm.nih.gov/pubmed/33869869 http://dx.doi.org/10.1016/j.heliyon.2021.e06673 |
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