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The role of clouds in improving the regression model for hourly values of diffuse solar radiation

Listed author(s):
  • Furlan, Claudia
  • de Oliveira, Amauri Pereira
  • Soares, Jacyra
  • Codato, Georgia
  • Escobedo, João Francisco
Registered author(s):

    The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R2=0.93 and RMSE=0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R2=0.92.

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    Article provided by Elsevier in its journal Applied Energy.

    Volume (Year): 92 (2012)
    Issue (Month): C ()
    Pages: 240-254

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    Handle: RePEc:eee:appene:v:92:y:2012:i:c:p:240-254
    DOI: 10.1016/j.apenergy.2011.10.032
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    1. Escobedo, João F. & Gomes, Eduardo N. & Oliveira, Amauri P. & Soares, Jacyra, 2009. "Modeling hourly and daily fractions of UV, PAR and NIR to global solar radiation under various sky conditions at Botucatu, Brazil," Applied Energy, Elsevier, vol. 86(3), pages 299-309, March.
    2. Munawwar, Saima & Muneer, Tariq, 2007. "Statistical approach to the proposition and validation of daily diffuse irradiation models," Applied Energy, Elsevier, vol. 84(4), pages 455-475, April.
    3. 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.
    4. Wong, L. T. & Chow, W. K., 2001. "Solar radiation model," Applied Energy, Elsevier, vol. 69(3), pages 191-224, July.
    5. Ortega, Alberto & Escobar, Rodrigo & Colle, Sergio & de Abreu, Samuel Luna, 2010. "The state of solar energy resource assessment in Chile," Renewable Energy, Elsevier, vol. 35(11), pages 2514-2524.
    6. Senkal, Ozan & Kuleli, Tuncay, 2009. "Estimation of solar radiation over Turkey using artificial neural network and satellite data," Applied Energy, Elsevier, vol. 86(7-8), pages 1222-1228, July.
    7. Jacovides, C.P. & Tymvios, F.S. & Assimakopoulos, V.D. & Kaltsounides, N.A., 2006. "Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation," Renewable Energy, Elsevier, vol. 31(15), pages 2492-2504.
    8. 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.
    9. Joshi, Anand S. & Dincer, Ibrahim & Reddy, Bale V., 2009. "Performance analysis of photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1884-1897, October.
    10. Arboit, M. & Diblasi, A. & Fernández Llano, J.C. & de Rosa, C., 2008. "Assessing the solar potential of low-density urban environments in Andean cities with desert climates: The case of the city of Mendoza, in Argentina," Renewable Energy, Elsevier, vol. 33(8), pages 1733-1748.
    11. Janjai, S. & Pankaew, P. & Laksanaboonsong, J., 2009. "A model for calculating hourly global solar radiation from satellite data in the tropics," Applied Energy, Elsevier, vol. 86(9), pages 1450-1457, September.
    12. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    13. Tiba, C. & Fraidenraich, N. & Grossi Gallegos, H. & Lyra, F.J.M., 2002. "Solar energy resource assessment — Brazil," Renewable Energy, Elsevier, vol. 27(3), pages 383-400.
    14. Jiang, Yingni, 2009. "Estimation of monthly mean daily diffuse radiation in China," Applied Energy, Elsevier, vol. 86(9), pages 1458-1464, September.
    15. Jain, P.K. & Lungu, E.M., 2002. "Stochastic models for sunshine duration and solar irradiation," Renewable Energy, Elsevier, vol. 27(2), pages 197-209.
    16. Desideri, Umberto & Proietti, Stefania & Sdringola, Paolo, 2009. "Solar-powered cooling systems: Technical and economic analysis on industrial refrigeration and air-conditioning applications," Applied Energy, Elsevier, vol. 86(9), pages 1376-1386, September.
    17. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    18. Thirugnanasambandam, Mirunalini & Iniyan, S. & Goic, Ranko, 2010. "A review of solar thermal technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 312-322, January.
    19. Boland, John & Ridley, Barbara & Brown, Bruce, 2008. "Models of diffuse solar radiation," Renewable Energy, Elsevier, vol. 33(4), pages 575-584.
    20. Alam, Shah & Kaushik, S.C. & Garg, S.N., 2009. "Assessment of diffuse solar energy under general sky condition using artificial neural network," Applied Energy, Elsevier, vol. 86(4), pages 554-564, April.
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