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

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  • Soares, Jacyra
  • Oliveira, Amauri P.
  • Boznar, Marija Zlata
  • Mlakar, Primoz
  • Escobedo, João F.
  • Machado, Antonio J.

Abstract

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.

Suggested Citation

  • Soares, Jacyra & Oliveira, Amauri P. & Boznar, Marija Zlata & Mlakar, Primoz & Escobedo, João F. & Machado, Antonio J., 2004. "Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique," Applied Energy, Elsevier, vol. 79(2), pages 201-214, October.
    • Handle: RePEc:eee:appene:v:79:y:2004:i:2:p:201-214
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    References listed on IDEAS

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    1. Oliveira, Amauri P. & Escobedo, João F. & Machado, Antonio J. & Soares, Jacyra, 2002. "Correlation models of diffuse solar-radiation applied to the city of São Paulo, Brazil," Applied Energy, Elsevier, vol. 71(1), pages 59-73, January.
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