Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility

In this paper, we present two methods for the synthetic generation of 1-min Direct Normal solar Irradiance (DNI) data from hourly means that can be applied globally without any local adaptation, which are based in the modelling of the stochastic component of DNI, and in the normalization of the dail...

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Autores: Larrañeta, Miguel, Fernández Peruchena, Carlos María, Silva Pérez, Manuel Antonio, Lillo Bravo, Isidoro
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/152961
Acceso en línea:https://hdl.handle.net/11441/152961
https://doi.org/10.1016/j.solener.2018.01.064
Access Level:acceso abierto
Palabra clave:DNI
High frequency
Solar radiation models
Cloud transients
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spelling Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibilityLarrañeta, MiguelFernández Peruchena, Carlos MaríaSilva Pérez, Manuel AntonioLillo Bravo, IsidoroDNIHigh frequencySolar radiation modelsCloud transientsIn this paper, we present two methods for the synthetic generation of 1-min Direct Normal solar Irradiance (DNI) data from hourly means that can be applied globally without any local adaptation, which are based in the modelling of the stochastic component of DNI, and in the normalization of the daily profiles. The similitude between measured and generated DNI distributions has been evaluated through the Kolmogorov-Smirnov test Integral (KSI), and its performance on the thermal power produced by a parabolic trough (PT) plant has been assessed using the daily normalized root mean square deviations (NRMSD) with respect to site measurements. The generation methods provide, for an annual 1-min synthetic data set, KSI values of ∼3.3 W/m2 and ∼12.9 W/m2 (depending on the generation method used), and daily NRMSD of ∼0.9% and ∼3.4%, respectively. Sites selected for validating these methods are located at different climates and latitudes, suggesting their global applicability.ElsevierIngeniería EnergéticaTEP122: Termodinámica y Energías Renovables2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/152961https://doi.org/10.1016/j.solener.2018.01.064reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésSolar Energy, 162, 573-584.https://www.sciencedirect.com/science/article/pii/S0038092X18300859info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1529612026-06-17T12:51:07Z
dc.title.none.fl_str_mv Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
title Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
spellingShingle Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
Larrañeta, Miguel
DNI
High frequency
Solar radiation models
Cloud transients
title_short Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
title_full Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
title_fullStr Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
title_full_unstemmed Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
title_sort Methodology to synthetically downscale DNI time series from 1-h to 1-min temporal resolution with geographic flexibility
dc.creator.none.fl_str_mv Larrañeta, Miguel
Fernández Peruchena, Carlos María
Silva Pérez, Manuel Antonio
Lillo Bravo, Isidoro
author Larrañeta, Miguel
author_facet Larrañeta, Miguel
Fernández Peruchena, Carlos María
Silva Pérez, Manuel Antonio
Lillo Bravo, Isidoro
author_role author
author2 Fernández Peruchena, Carlos María
Silva Pérez, Manuel Antonio
Lillo Bravo, Isidoro
author2_role author
author
author
dc.contributor.none.fl_str_mv Ingeniería Energética
TEP122: Termodinámica y Energías Renovables
dc.subject.none.fl_str_mv DNI
High frequency
Solar radiation models
Cloud transients
topic DNI
High frequency
Solar radiation models
Cloud transients
description In this paper, we present two methods for the synthetic generation of 1-min Direct Normal solar Irradiance (DNI) data from hourly means that can be applied globally without any local adaptation, which are based in the modelling of the stochastic component of DNI, and in the normalization of the daily profiles. The similitude between measured and generated DNI distributions has been evaluated through the Kolmogorov-Smirnov test Integral (KSI), and its performance on the thermal power produced by a parabolic trough (PT) plant has been assessed using the daily normalized root mean square deviations (NRMSD) with respect to site measurements. The generation methods provide, for an annual 1-min synthetic data set, KSI values of ∼3.3 W/m2 and ∼12.9 W/m2 (depending on the generation method used), and daily NRMSD of ∼0.9% and ∼3.4%, respectively. Sites selected for validating these methods are located at different climates and latitudes, suggesting their global applicability.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/152961
https://doi.org/10.1016/j.solener.2018.01.064
url https://hdl.handle.net/11441/152961
https://doi.org/10.1016/j.solener.2018.01.064
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Solar Energy, 162, 573-584.
https://www.sciencedirect.com/science/article/pii/S0038092X18300859
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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