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Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics

A novel method to extract the seven parameters of the double-diode model of solar cells using the current–voltage (I-V) characteristics under illumination and in the dark is presented. The algorithm consists of two subroutines which are alternatively run to adjust all the parameters of the cell in a...

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Autores principales: Montalvo-Galicia, Fredy, Sanz-Pascual, María Teresa, Rosales-Quintero, Pedro, Moreno-Moreno, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227553/
https://www.ncbi.nlm.nih.gov/pubmed/35745294
http://dx.doi.org/10.3390/nano12121955
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author Montalvo-Galicia, Fredy
Sanz-Pascual, María Teresa
Rosales-Quintero, Pedro
Moreno-Moreno, Mario
author_facet Montalvo-Galicia, Fredy
Sanz-Pascual, María Teresa
Rosales-Quintero, Pedro
Moreno-Moreno, Mario
author_sort Montalvo-Galicia, Fredy
collection PubMed
description A novel method to extract the seven parameters of the double-diode model of solar cells using the current–voltage (I-V) characteristics under illumination and in the dark is presented. The algorithm consists of two subroutines which are alternatively run to adjust all the parameters of the cell in an iterative process. Curve fitting of the light I-V characteristics ensures accuracy in the prediction of the maximum power point, whereas simultaneously fitting the dark I-V characteristics results in a set of physically meaningful parameters that provide information about the physical performance of the photovoltaic devices. Experimental I-V curves of in-house solar cells are used to validate the proposed parameter extraction method, which can be furthermore applied to other types of p–n junction-based photovoltaic devices.
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spelling pubmed-92275532022-06-25 Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics Montalvo-Galicia, Fredy Sanz-Pascual, María Teresa Rosales-Quintero, Pedro Moreno-Moreno, Mario Nanomaterials (Basel) Article A novel method to extract the seven parameters of the double-diode model of solar cells using the current–voltage (I-V) characteristics under illumination and in the dark is presented. The algorithm consists of two subroutines which are alternatively run to adjust all the parameters of the cell in an iterative process. Curve fitting of the light I-V characteristics ensures accuracy in the prediction of the maximum power point, whereas simultaneously fitting the dark I-V characteristics results in a set of physically meaningful parameters that provide information about the physical performance of the photovoltaic devices. Experimental I-V curves of in-house solar cells are used to validate the proposed parameter extraction method, which can be furthermore applied to other types of p–n junction-based photovoltaic devices. MDPI 2022-06-07 /pmc/articles/PMC9227553/ /pubmed/35745294 http://dx.doi.org/10.3390/nano12121955 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Montalvo-Galicia, Fredy
Sanz-Pascual, María Teresa
Rosales-Quintero, Pedro
Moreno-Moreno, Mario
Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics
title Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics
title_full Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics
title_fullStr Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics
title_full_unstemmed Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics
title_short Solar Cell Parameter Extraction Method from Illumination and Dark I-V Characteristics
title_sort solar cell parameter extraction method from illumination and dark i-v characteristics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227553/
https://www.ncbi.nlm.nih.gov/pubmed/35745294
http://dx.doi.org/10.3390/nano12121955
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