Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique
Carregando...
Fonte externa
Fonte externa
Data
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Elsevier B.V.
Tipo
Artigo
Direito de acesso
Acesso restrito
Fonte externa
Fonte externa
Resumo
dIn this work, a perceptron neural-network technique is applied to estimate hourly values of the diffuse solar-radiation at the surface in São Paulo City, Brazil, using as input the global solar-radiation and other meteorological parameters measured from 1998 to 2001. The neural-network verification was performed using the hourly measurements of diffuse solar-radiation obtained during the year 2002. The neural network was developed based on both feature determination and pattern selection techniques. It was found that the inclusion of the atmospheric long-wave radiation as input improves the neural-network performance. on the other hand traditional meteorological parameters, like air temperature and atmospheric pressure, are not as important as long-wave radiation which acts as a surrogate for cloud-cover information on the regional scale. An objective evaluation has shown that the diffuse solar-radiation is better reproduced by neural network synthetic series than by a correlation model. (C) 2004 Elsevier Ltd. All rights reserved.
Descrição
Palavras-chave
hourly diffuse solar radiation, perceptron neural network, São Paulo City
Idioma
Inglês
Citação
Applied Energy. Oxford: Elsevier B.V., v. 79, n. 2, p. 201-214, 2004.
