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Estimation of hourly solar radiation for India

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  • Parishwad, G.V.
  • Bhardwaj, R.K.
  • Nema, V.K.

Abstract

The ASHRAE constants predict high values of the hourly beam radiation and very low values of the hourly diffuse radiation when used to predict radiation at Indian locations. Hence a procedure has been developed for the estimation of direct, diffuse and global hourly solar radiation on a horizontal surface for any location in India. To calculate hourly solar radiation, an exponential curve, similar to the one used by ASHRAE, was fitted to the measured solar radiation data of six cities from different regions of India. The statistical analysis was carried out for the data computed using ASHRAE constants and the set of constants obtained for India using the measured data of four different Indian cities selected randomly. Three statistical indicators were used to compare the accuracy of the developed procedure. The results show that ASHRAE constants are not suitable to estimate hourly solar radiation in India. Hourly solar radiation estimated by constants obtained for India are fairly comparable with measured data. The mean percentage error with Indian constants for these four Indian cities was found as low as 2.27, −6.29 and −6.09% for hourly beam, diffuse and global radiation, respectively.

Suggested Citation

  • Parishwad, G.V. & Bhardwaj, R.K. & Nema, V.K., 1997. "Estimation of hourly solar radiation for India," Renewable Energy, Elsevier, vol. 12(3), pages 303-313.
    • Handle: RePEc:eee:renene:v:12:y:1997:i:3:p:303-313
    DOI: 10.1016/S0960-1481(97)00039-6
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    References listed on IDEAS

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    1. Zeroual, A. & Ankrim, M. & Wilkinson, A.J., 1996. "The diffuse-global correlation: Its application to estimating solar radiation on tilted surfaces in Marrakesh, Morocco," Renewable Energy, Elsevier, vol. 7(1), pages 1-13.
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    1. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    2. Karakoti, Indira & Das, Prasun Kumar & Singh, S.K., 2012. "Predicting monthly mean daily diffuse radiation for India," Applied Energy, Elsevier, vol. 91(1), pages 412-425.
    3. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    4. Mohanty, Sthitapragyan & Patra, Prashanta K. & Sahoo, Sudhansu S. & Mohanty, Asit, 2017. "Forecasting of solar energy with application for a growing economy like India: Survey and implication," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 539-553.
    5. Chang, Kai & Zhang, Qingyuan, 2019. "Improvement of the hourly global solar model and solar radiation for air-conditioning design in China," Renewable Energy, Elsevier, vol. 138(C), pages 1232-1238.
    6. Jamil, Basharat & Akhtar, Naiem, 2017. "Estimation of diffuse solar radiation in humid-subtropical climatic region of India: Comparison of diffuse fraction and diffusion coefficient models," Energy, Elsevier, vol. 131(C), pages 149-164.
    7. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparative analysis of diffuse solar radiation models based on sky-clearness index and sunshine period for humid-subtropical climatic region of India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 329-355.
    8. Parishwad, G.V. & Bhardwaj, R.K. & Nema, V.K., 1998. "Effect of rainfall on the estimation of monthly mean hourly solar radiation for India," Renewable Energy, Elsevier, vol. 13(4), pages 505-521.
    9. Cuce, Erdem & Cuce, Pinar Mert, 2013. "A comprehensive review on solar cookers," Applied Energy, Elsevier, vol. 102(C), pages 1399-1421.
    10. Seyed Abbas Mousavi Maleki & H. Hizam & Chandima Gomes, 2017. "Estimation of Hourly, Daily and Monthly Global Solar Radiation on Inclined Surfaces: Models Re-Visited," Energies, MDPI, vol. 10(1), pages 1-28, January.
    11. Polasek, Tomas & Čadík, Martin, 2023. "Predicting photovoltaic power production using high-uncertainty weather forecasts," Applied Energy, Elsevier, vol. 339(C).

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