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Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique

2004; Elsevier BV; Volume: 79; Issue: 2 Linguagem: Inglês

10.1016/j.apenergy.2003.11.004

1872-9118

Jacyra Soares, Amauri Pereira de Oliveira, Marija Zlata Božnar, Primož Mlakar, João Francisco Escobedo, Antonio J. Machado,

Advanced Image Fusion Techniques

In 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.