Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique
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Data
2004-10-01
Autores
Soares, J.
Oliveira, A. P.
Boznar, M. Z.
Mlakar, P.
Escobedo, João Francisco [UNESP]
Machado, A. J.
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Elsevier B.V.
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.
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hourly diffuse solar radiation, perceptron neural network, São Paulo City
Como citar
Applied Energy. Oxford: Elsevier B.V., v. 79, n. 2, p. 201-214, 2004.