The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction

In the search to optimize electricity generation systems based on renewable energy sources, solar power plants are a clear alternative for reducing pollution on the planet. In particular, concentrating solar power plants with central tower technology supply energy to large population centers and the...

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Autores: Alonso Montesinos, Joaquín, Ballestrín, Jesús, López Rodríguez, Gabriel, Carra, Elena, Polo, Jesús, Marzo, Aitor, Barbero, Javier, Batlles, Francisco Javier
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Huelva (UHU)
Repositorio:Arias Montano. Repositorio Institucional de la Universidad de Huelva
Idioma:inglés
OAI Identifier:oai:ariasmontano.uhu.es:10272/24563
Acceso en línea:https://hdl.handle.net/10272/24563
Access Level:acceso abierto
Palabra clave:Atmospheric Extinction
Solar energy
Image processing
CSP plants
PV plants
ANN
2501 Ciencias de la Atmósfera
3322 Tecnología Energética
1203.04 Inteligencia Artificial
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oai_identifier_str oai:ariasmontano.uhu.es:10272/24563
network_acronym_str ES
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repository_id_str
spelling The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinctionAlonso Montesinos, JoaquínBallestrín, JesúsLópez Rodríguez, GabrielCarra, ElenaPolo, JesúsMarzo, AitorBarbero, JavierBatlles, Francisco JavierAtmospheric ExtinctionSolar energyImage processingCSP plantsPV plantsANN2501 Ciencias de la Atmósfera3322 Tecnología Energética1203.04 Inteligencia ArtificialIn the search to optimize electricity generation systems based on renewable energy sources, solar power plants are a clear alternative for reducing pollution on the planet. In particular, concentrating solar power plants with central tower technology supply energy to large population centers and they are generally located at desert sites. Production in these plants drops due to the presence of particles in the environment. These particles are complex to measure and doing so usually requires the use of dedicated, expensive instrumentation. In this work, we present a methodology called Extinction that estimates this attenuation phenomenon utilizing meteorological variables, along with the use of artificial neural networks (ANN). Direct normal irradiance, relative humidity, temperature and pressure have been the only meteorological variables needed to estimate the Extinction. The results from the estimations presented a correlation coefficient value (R) of 0.88 (between the measured and estimated atmospheric horizontal extinction with ANN), a normalized Mean Bias Error (nMBE) of 0% and a normalized Root-Mean Square Deviation (nRMSD) of 7%.Elsevier20212021-02-2020212021-02-20journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10272/24563reponame:Arias Montano. Repositorio Institucional de la Universidad de Huelvainstname:Universidad de Huelva (UHU)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:ariasmontano.uhu.es:10272/245632026-06-02T14:58:11Z
dc.title.none.fl_str_mv The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
title The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
spellingShingle The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
Alonso Montesinos, Joaquín
Atmospheric Extinction
Solar energy
Image processing
CSP plants
PV plants
ANN
2501 Ciencias de la Atmósfera
3322 Tecnología Energética
1203.04 Inteligencia Artificial
title_short The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
title_full The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
title_fullStr The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
title_full_unstemmed The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
title_sort The use of ANN and conventional solar-plant meteorological variables to estimate atmospheric horizontal extinction
dc.creator.none.fl_str_mv Alonso Montesinos, Joaquín
Ballestrín, Jesús
López Rodríguez, Gabriel
Carra, Elena
Polo, Jesús
Marzo, Aitor
Barbero, Javier
Batlles, Francisco Javier
author Alonso Montesinos, Joaquín
author_facet Alonso Montesinos, Joaquín
Ballestrín, Jesús
López Rodríguez, Gabriel
Carra, Elena
Polo, Jesús
Marzo, Aitor
Barbero, Javier
Batlles, Francisco Javier
author_role author
author2 Ballestrín, Jesús
López Rodríguez, Gabriel
Carra, Elena
Polo, Jesús
Marzo, Aitor
Barbero, Javier
Batlles, Francisco Javier
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv Atmospheric Extinction
Solar energy
Image processing
CSP plants
PV plants
ANN
2501 Ciencias de la Atmósfera
3322 Tecnología Energética
1203.04 Inteligencia Artificial
topic Atmospheric Extinction
Solar energy
Image processing
CSP plants
PV plants
ANN
2501 Ciencias de la Atmósfera
3322 Tecnología Energética
1203.04 Inteligencia Artificial
description In the search to optimize electricity generation systems based on renewable energy sources, solar power plants are a clear alternative for reducing pollution on the planet. In particular, concentrating solar power plants with central tower technology supply energy to large population centers and they are generally located at desert sites. Production in these plants drops due to the presence of particles in the environment. These particles are complex to measure and doing so usually requires the use of dedicated, expensive instrumentation. In this work, we present a methodology called Extinction that estimates this attenuation phenomenon utilizing meteorological variables, along with the use of artificial neural networks (ANN). Direct normal irradiance, relative humidity, temperature and pressure have been the only meteorological variables needed to estimate the Extinction. The results from the estimations presented a correlation coefficient value (R) of 0.88 (between the measured and estimated atmospheric horizontal extinction with ANN), a normalized Mean Bias Error (nMBE) of 0% and a normalized Root-Mean Square Deviation (nRMSD) of 7%.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-02-20
2021
2021-02-20
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10272/24563
url https://hdl.handle.net/10272/24563
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-SinDerivadas 3.0 España
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-SinDerivadas 3.0 España
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Arias Montano. Repositorio Institucional de la Universidad de Huelva
instname:Universidad de Huelva (UHU)
instname_str Universidad de Huelva (UHU)
reponame_str Arias Montano. Repositorio Institucional de la Universidad de Huelva
collection Arias Montano. Repositorio Institucional de la Universidad de Huelva
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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