Computational statistical analysis of the wind and solar potential for electricity generation
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , |
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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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 |