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Prediction of direct and global solar irradiance using broadband models: Validation of REST model

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  • Alam, Shah

Abstract

In the present paper, three parametric models Yang, CPCR2 and REST (without considering transmittance due to nitrogen dioxide) have been analyzed for four Indian stations, namely New Delhi, Mumbai, Pune and Jaipur over the period of 1995–2002, under cloudless conditions. These stations have different climatic conditions. The beam radiation at normal incidence as well as global solar radiation at horizontal surface was computed for these locations during all seasons except monsoon (June to September). The computed values of beam and global irradiance was compared with reference values in case of beam and measured values in case of global solar radiation on the basis of percentage root mean square error (RMSE) and mean bias error (MBE). The maximum RMSE is 6.5% in REST model, as compare to 15% in Yang and 11% in CPCR2 model for predicting direct normal irradiance. The predicted global radiation at horizontal is showing maximum RMSE 7% in REST model, 13.4% in Yang and 25.9% in CPCR2 model. This shows that REST model has good agreement with measured data for these Indian stations as compare to other two models.

Suggested Citation

  • Alam, Shah, 2006. "Prediction of direct and global solar irradiance using broadband models: Validation of REST model," Renewable Energy, Elsevier, vol. 31(8), pages 1253-1263.
    • Handle: RePEc:eee:renene:v:31:y:2006:i:8:p:1253-1263
    DOI: 10.1016/j.renene.2005.06.009
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    1. Wong, L. T. & Chow, W. K., 2001. "Solar radiation model," Applied Energy, Elsevier, vol. 69(3), pages 191-224, July.
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    1. Reno, Matthew J. & Hansen, Clifford W., 2016. "Identification of periods of clear sky irradiance in time series of GHI measurements," Renewable Energy, Elsevier, vol. 90(C), pages 520-531.
    2. Janjai, S. & Sricharoen, K. & Pattarapanitchai, S., 2011. "Semi-empirical models for the estimation of clear sky solar global and direct normal irradiances in the tropics," Applied Energy, Elsevier, vol. 88(12), pages 4749-4755.
    3. Purohit, Ishan & Purohit, Pallav, 2015. "Inter-comparability of solar radiation databases in Indian context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 735-747.
    4. Jiang, Yingni, 2008. "Prediction of monthly mean daily diffuse solar radiation using artificial neural networks and comparison with other empirical models," Energy Policy, Elsevier, vol. 36(10), pages 3833-3837, October.
    5. Younes, S. & Muneer, T., 2007. "Clear-sky classification procedures and models using a world-wide data-base," Applied Energy, Elsevier, vol. 84(6), pages 623-645, June.
    6. Srivastava, Raj Shekhar & Kumar, Anuruddh & Thakur, Harishchandra & Vaish, Rahul, 2022. "Solar assisted thermoelectric cooling/heating system for vehicle cabin during parking: A numerical study," Renewable Energy, Elsevier, vol. 181(C), pages 384-403.

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