Computational statistical analysis of the wind and solar potential for electricity generation

Detalhes bibliográficos
Autor(a) principal: Silva, Ricardo Ezequiel
Data de Publicação: 2012
Outros Autores: Fagundes, Regiane Slongo, Ferruzzi, Yurri
Tipo de documento: Artigo
Idioma: por
Título da fonte: Vetor (Online)
Texto Completo: https://periodicos.furg.br/vetor/article/view/2067
Resumo: This paper describes an application developed through scientific project initiation. The aim is to provide information to assess the energy potential of renewable energy such as wind and solar radiation. The information submitted by the program are obtained from weather stations that collect data on temperature, wind speed and intensity of solar radiation. The data is processed using statistical techniques that allow to summarize a large volume of measurements. The result is information presented in tables, graphs and reports, which measure the energy output of these alternative sources in electricity generation.
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spelling Computational statistical analysis of the wind and solar potential for electricity generationAnálise ComputacionalPotencial energéticoEletricidade.This paper describes an application developed through scientific project initiation. The aim is to provide information to assess the energy potential of renewable energy such as wind and solar radiation. The information submitted by the program are obtained from weather stations that collect data on temperature, wind speed and intensity of solar radiation. The data is processed using statistical techniques that allow to summarize a large volume of measurements. The result is information presented in tables, graphs and reports, which measure the energy output of these alternative sources in electricity generation.Universidade Federal do Rio Grande2012-04-25info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.furg.br/vetor/article/view/2067VETOR - Journal of Exact Sciences and Engineering; Vol. 20 No. 2 (2010); 83-91VETOR - Revista de Ciências Exatas e Engenharias; v. 20 n. 2 (2010); 83-912358-34520102-7352reponame:Vetor (Online)instname:Universidade Federal do Rio Grande (FURG)instacron:FURGporhttps://periodicos.furg.br/vetor/article/view/2067/1376Copyright (c) 2014 VETOR - Revista de Ciências Exatas e Engenhariasinfo:eu-repo/semantics/openAccessSilva, Ricardo EzequielFagundes, Regiane SlongoFerruzzi, Yurri2023-03-22T15:42:43Zoai:periodicos.furg.br:article/2067Revistahttps://periodicos.furg.br/vetorPUBhttps://periodicos.furg.br/vetor/oaigmplatt@furg.br2358-34520102-7352opendoar:2023-03-22T15:42:43Vetor (Online) - Universidade Federal do Rio Grande (FURG)false
dc.title.none.fl_str_mv Computational statistical analysis of the wind and solar potential for electricity generation
title Computational statistical analysis of the wind and solar potential for electricity generation
spellingShingle Computational statistical analysis of the wind and solar potential for electricity generation
Silva, Ricardo Ezequiel
Análise Computacional
Potencial energético
Eletricidade.
title_short Computational statistical analysis of the wind and solar potential for electricity generation
title_full Computational statistical analysis of the wind and solar potential for electricity generation
title_fullStr Computational statistical analysis of the wind and solar potential for electricity generation
title_full_unstemmed Computational statistical analysis of the wind and solar potential for electricity generation
title_sort Computational statistical analysis of the wind and solar potential for electricity generation
author Silva, Ricardo Ezequiel
author_facet Silva, Ricardo Ezequiel
Fagundes, Regiane Slongo
Ferruzzi, Yurri
author_role author
author2 Fagundes, Regiane Slongo
Ferruzzi, Yurri
author2_role author
author
dc.contributor.author.fl_str_mv Silva, Ricardo Ezequiel
Fagundes, Regiane Slongo
Ferruzzi, Yurri
dc.subject.por.fl_str_mv Análise Computacional
Potencial energético
Eletricidade.
topic Análise Computacional
Potencial energético
Eletricidade.
description This paper describes an application developed through scientific project initiation. The aim is to provide information to assess the energy potential of renewable energy such as wind and solar radiation. The information submitted by the program are obtained from weather stations that collect data on temperature, wind speed and intensity of solar radiation. The data is processed using statistical techniques that allow to summarize a large volume of measurements. The result is information presented in tables, graphs and reports, which measure the energy output of these alternative sources in electricity generation.
publishDate 2012
dc.date.none.fl_str_mv 2012-04-25
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.furg.br/vetor/article/view/2067
url https://periodicos.furg.br/vetor/article/view/2067
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.furg.br/vetor/article/view/2067/1376
dc.rights.driver.fl_str_mv Copyright (c) 2014 VETOR - Revista de Ciências Exatas e Engenharias
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2014 VETOR - Revista de Ciências Exatas e Engenharias
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio Grande
publisher.none.fl_str_mv Universidade Federal do Rio Grande
dc.source.none.fl_str_mv VETOR - Journal of Exact Sciences and Engineering; Vol. 20 No. 2 (2010); 83-91
VETOR - Revista de Ciências Exatas e Engenharias; v. 20 n. 2 (2010); 83-91
2358-3452
0102-7352
reponame:Vetor (Online)
instname:Universidade Federal do Rio Grande (FURG)
instacron:FURG
instname_str Universidade Federal do Rio Grande (FURG)
instacron_str FURG
institution FURG
reponame_str Vetor (Online)
collection Vetor (Online)
repository.name.fl_str_mv Vetor (Online) - Universidade Federal do Rio Grande (FURG)
repository.mail.fl_str_mv gmplatt@furg.br
_version_ 1797041761228423168

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