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Estimating global solar radiation using common meteorological data in Akure, Nigeria

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  • Adaramola, Muyiwa S.

Abstract

In this study, the global solar radiation on horizontal surface in Akure, Nigeria (Latitude 7.25° N and Longitude 5.2° E) using 22-year data (July 1983–June 2005) was analysed. Simple empirical correlations for evaluating the monthly average daily global solar radiation were developed. The calculated monthly clearness index values indicates that prevailing weather condition in Akure is partly overcast but can become heavily overcast during the months of July–September. The Angstrom–Page correlation predicted the monthly average daily global solar radiation better than the other correlations developed in this study. However, in the absence of the sunshine hour data, it was found that temperature only based correlations (especially the average temperature based correlation) and precipitation based correlation can be used to predict the global solar radiation within reasonable level of accuracy in Akure. The correlations presented in this study could be applied to locations with comparable weather condition to Akure.

Suggested Citation

  • Adaramola, Muyiwa S., 2012. "Estimating global solar radiation using common meteorological data in Akure, Nigeria," Renewable Energy, Elsevier, vol. 47(C), pages 38-44.
    • Handle: RePEc:eee:renene:v:47:y:2012:i:c:p:38-44
    DOI: 10.1016/j.renene.2012.04.005
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    References listed on IDEAS

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    1. Yohanna, Jonathan K. & Itodo, Isaac N. & Umogbai, Victor I., 2011. "A model for determining the global solar radiation for Makurdi, Nigeria," Renewable Energy, Elsevier, vol. 36(7), pages 1989-1992.
    2. Almorox, J. & Hontoria, C. & Benito, M., 2011. "Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain)," Applied Energy, Elsevier, vol. 88(5), pages 1703-1709, May.
    3. Gopinathan, K.K. & Soler, Alfonso, 1992. "A sunshine dependent global insolation model for latitudes between 60°N and 70°N," Renewable Energy, Elsevier, vol. 2(4), pages 401-404.
    4. Chineke, Theo Chidiezie, 2008. "Equations for estimating global solar radiation in data sparse regions," Renewable Energy, Elsevier, vol. 33(4), pages 827-831.
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