2016
DOI: 10.5902/2179460x20233
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Comparação Entre Os Dados De Vento Das Reanálises Meteorológicas Era-Interim E CFSR Com Os Dados Das Estações Automáticas Do Inmet No Rio Grande Do Sul

Abstract: A energia eólica é, atualmente, uma das fontes de eletricidade que mais crescem em todo o mundo. Porém, especialmente no Brasil, ainda é muito difícil a localização de regiões com ventos confiáveis para a implantação de um parque eólico pois não existe uma densidade de dados válidos que sirvam de garantia de eficiência do parque. Assim, o desenvolvimento de modelos que simulam as condições de vento são extremamente importantes para estudos e pesquisas na área. Neste sentido, dados de reanálises

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Cited by 5 publications
(3 citation statements)
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“…The model's vertical resolution currently comprises 60 levels, whose highest level is 0.1hPa. It is updated twice a day: 00:00 UTC and 12:00 UTC, although the four synoptic times are made available: 00:00 UTC, 06:00 UTC, 12:00 UTC, and 18:00 UTC (Stüker et al, 2016).…”
Section: Methodsmentioning
confidence: 99%
“…The model's vertical resolution currently comprises 60 levels, whose highest level is 0.1hPa. It is updated twice a day: 00:00 UTC and 12:00 UTC, although the four synoptic times are made available: 00:00 UTC, 06:00 UTC, 12:00 UTC, and 18:00 UTC (Stüker et al, 2016).…”
Section: Methodsmentioning
confidence: 99%
“…On the other hand, in Brazil, challenges have been highlighted in locating regions with reliable winds for wind farm implementation due to the scarcity of valid data ensuring park efficiency [25]. Concerning the establishment of wind farms, the significance of various stages, including determining the installation site, assessing local wind potential, identifying wind power, and predicting wind power generation, has been underscored [26].…”
Section: Electrical-infrastructure Layermentioning
confidence: 99%
“…Esta média representa o valor predominante daquele elemento no local considerado. As normais utilizadas neste trabalho se obtidas da reanálise do European Center for Medium-Range Weather Forecasts (ERA5)(STÜKER et al, 2016;LIMBERGER;SILVA, 2018).…”
unclassified