Estimation of Global Solar Radiation Using Empirical Models

Author(s): Onyeka V. O.1, Nwobi-Okoye C. C.1, Okafor O. C.2*, Madu K. E.1, Mbah O. M.3

1 Chukwuemeka Odumegwu Ojukwu University, Uli, Anambra State, Nigeria;
2 Grundtvig Polytechnic, Oba, Anambra State, Nigeria;
3 Federal University Oye, Ekiti State, Nigeria

*Corresponding Author’s Address: [email protected]

Issue: Volume 8, Issue 2 (2021)

Submitted: September 8, 2021
Accepted for publication: December 10, 2021
Available online: December 15, 2021

Onyeka V. O., Nwobi-Okoye C. C., Okafor O. C., Madu K. E., Mbah O. M. (2021). Estimation of global solar radiation using empirical models. Journal of Engineering Sciences, Vol. 8(2), pp. G11-G24, doi: 10.21272/jes.2021.8(2).g2

DOI: 10.21272/jes.2021.8(2).g2

Research Area:  CHEMICAL ENGINEERING: Advanced Energy Efficient Technologies

Abstract. The dearth of solar radiation data availability has necessitated the development of several mathematical models for estimating global solar radiation (GSR) of regions using the readily available meteorological data of the region. This study was centered on estimating the GSR of the Ihiala region in Sub-Saharan Africa using empirical models. For the last ten years, meteorological data from the Nigerian Meteorological Agency (NIMET) were used. The sunshine-based equation, temperature-based equation, and multivariate polynomial equations were the empirical models employed to estimate the GSR of the region. The performance of the seven models was determined using statistical measures. From the results obtained, the seven models had their respective P-values all less than 5 % significant level for a confidence interval of 95 %. Thereby attesting their suitability for GSR estimation of the region is needed. Also, from the other statistical tools employed, the considered multivariate model had better estimation performance than the other models. Therefore, the considered multivariate model is suitable for estimating the GSR of the Ihiala region in Sub-Saharan Africa.

Keywords: renewable energy, global solar radiation, artificial neural network, statistical tests.


  1. Appelbaum, J. (2001). Photovoltaics: Present and Future, a Seminar Series. Katholieke Universiteit, Leuven, Belgium.
  2. Mandalia, H. C., Jain, V. K., Pattanaik, B. N. (2012). Application of Super-molecules in solar energy conversion: A review. Research Journal of Chemical Science, Vol. 2(1), pp. 89-102.
  3. Abdulrahim, A. T., Diso, I. S., El-Jummah, A.M. (2011). Solar concentrators’ developments in Nigeria: A review. Continental Journal of Engineering Sciences, Vol. 6(3), pp. 30-37.
  4. Page, J. K., (1964). The estimation of monthly mean values of daily total short-wave radiation on vertical and inclined surfaces from sunshine records. Proceeding of the UN Conference on New Sources of Energy, p. 98.
  5. Trabea, A. A., Shaltout M. A., (2000). Correlation of global solar-radiation with meteorological parameters over Egypt. Renewable Energy, Vol. 21, pp. 297-308.
  6. Dimas, F. A. R., Syed, I. U. H. G., Mohd, S. A. (2011). Hourly solar radiation estimation using ambient temperature and relative humidity data. International Journal of Environment Science and Development, Vol. 2(3), pp. 188-193.
  7. Khem, P. N., Bhattarai, B. K., Sapkota, B., Kjeldstad, B. (2012). Estimation of global solar radiation using sunshine duration in Himalaya region. Research Journal of Chemical Sciences, Vol. 2(11), pp. 20-25.
  8. Mbah, O. M., Ozor,P., Mgbemene, C., Enibe, S. O., Mbohwa, C. (2018). Comparison of experimental data and isotropic sky models for global solar radiation estimation in Eastern Nigeria. World Congress on Engineering, WCE 2018, paper no. ICME_107.
  9. Mbah, O. M., Ozor, P., Mgbemene, C., Enibe, S. O., Mbohwa, C. (2018). Comparative analysis of anisotropic sky models and experimental data in estimating solar radiation on tilted surface in Sub-Saharan African climate. IEOM Conference. IEOM 2018, pp. 592-598.
  10. Aruna, R. K., Janarthanan, B. (2014). Study of clearness and cloudiness index at tropical locations. International Journal of Scientific and Engineering Research, Vol. 5(2), 161.
  11. Prescott, J. A. (1940). Evaporation from a water surface in relation to solar radiation. Journal of Energy Technology, Vol. 64, pp. 114-148.
  12. Page, J. K. (1961). The estimation of monthly mean values of daily total short wave radiation on vertical and inclined surface from sunshine records for latitude 40N-40S. Proceedings of UN Conference on New Sources of Energy, Vol. 4(598), pp. 378-390.
  13. Cohen, J., Cohen, P., West, S. G., Aiken, L. S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates, New Jersey, USA, pp. 168-174.
  14. Cooper, P. I., (1969). The absorption of radiation in solar stills. Solar Energy, Vol. 12(3), pp. 333-346.
  15. Duffie, J. A., Beckman, W. A. (2013). Solar Engineering of Thermal Processes. John Wiley and Sons, New York, USA.
  16. Robaa, S. M. (2008). Evaluation of sunshine duration from cloud data in Egypt. Energy, Vol. 33, pp. 785-795.
  17. Glover, J., McCulloch, J. S. (1958). The empirical relation between solar radiation and hours of sunshine. Journal of Royal Meteorological Society, Vol. 84, pp. 172-175.
  18. Chen, R., Ersi, K., Yang, J., Lu, S., Zhao, W. (2004). Validation of five global radiation models with measured daily data in China. Energy Conversion and Management, Vol. 45, pp. 1759-1769.

Full Text