New temperature dependent models for estimating global solar radiation across the midland climatic zone of Nigeria

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Authentic information of the availability of global solar radiation is significant to agro/hydro meteorologists, atmospheric Physicists and solar energy engineers for the purpose of local and international marketing, designs and manufacturing of solar equipment. In this study, five new proposed temperature dependent models were evaluated using measured monthly average daily global solar radiation, maximum and minimum temperature meteorological data during the period of thirty one years (1980-2010). The new models were compared with three existing temperature dependent models (Chen et al., Hargreaves and Samani and Garcia) using seven different statistical validation indicators of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test, Nash – Sutcliffe Equation (NSE) and Index of Agreement (IA) to ascertain the suitability of global solar radiation estimation in five different locations (Zaria, Bauchi, Jos, Minna and Yola) situated in the Midland climatic zone of Nigeria. In each location, the result shows that a new empirical regression model was found more accurate when compared to the existing models and are therefore recommended for estimating global solar radiation in the location and regions with similar climatic information where only temperature data are available. The evaluated existing Hargreaves and Samani and Garcia temperature based models for Jos were compared to those available in literature and was found more suitable for estimating global solar radiation for the location. The comparison between the measured and estimated temperature dependent models depicts slight overestimation and underestimation in some months with good fitting in the studied locations. However, the recommended models give the best fitting.




  • Keywords

    Global Solar Radiation; Meteorological Data; Midland Climatic Zone; Statistical Validation Indicators; Temperature Dependent Models.

  • References

      [1] B. M. Olomiyesan, O. D. Oyedum, P. E. Ugwuoke, J. A. Ezenwora, A.G. Ibrahim, Solar Energy for Power Generation: A Review of Solar Radiation Measurement Processes and Global Solar Radiation Modelling Techniques. Nigerian Journal of Solar Energy, Vol. 26 (2015) Pp 1 – 8.

      [2] B. M. Olomiyesan, O. D. Oyedum, Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria. Hindawi Publishing Corporation. Journal of Solar Energy Volume 2016 (2016) Article ID 8197389, 7 pages

      [3] A. Ångström, Solar and terrestrial radiation. Quarterly Journal of the Royal Meteorological society, 50 (1924) 121-125.

      [4] J. K. Page, The estimation of monthly mean values of daily total short – wave radiation on vertical and inclined surfaces from sunshine records for latitude - . Proceeding of the UN Conference on New Sources of Energy, Rome, 4 (1964) 378 – 390.

      [5] Y. K. Sanusi, S. G. Abisoye, Estimation of Solar Radiation at Ibadan, Nigeria, Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS), 2, 4 (2011) 701 – 705.

      [6] L. Huashan, C. Fei, W. Xianlong, M. Weibin, A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China. Hindawi Publishing Corporation. The Scientific World Journal, Volume 2014 (2014) 1 – 9.

      [7] D. N. Girma, Estimation of Monthly Average Daily Solar Radiation from Meteorological Parameters: Sunshine Hours and Measured Temperature in Tepi, Ethiopia. International Journal of Energy and Environmental Science. Vol. 3, No. 1 (2018) 19-26.

      [8] WMO, A Note on Climatological Normal. Technical Note. World Meteorological Organization, Geneva, Switzerland. (1967).

      [9] O. S. Ojo, B. Adeyemi, Estimation of Solar Radiation using Air Temperature and Geographical Coordinate over Nigeria, The Pacific Journal of Science and Technology, 15, 2 (2014) 78 – 88.

      [10] M. Iqbal, An introduction to solar radiation, first ed. Academic Press, New York. (1983)

      [11] S. Zekai, Solar energy fundamentals and modeling techniques: atmosphere, Environment, climate change and renewable energy, first ed. Springer, London. (2008)

      [12] E. O. Falayi, A. B. Rabiu, R. O. Teliat, Correlations to estimate monthly mean of daily diffuse solar radiation in some selected cities in Nigeria, Pelagia Research Library, 2, 4 (2011) 480-490.

      [13] R. Chen, K. Ersi, J. Yang, S. Lu, W. Zhao, Validation of five global radiation Models with measured daily data in China. Energy Conversion and Management, 45 (2004) 1759-1769.

      [14] G. Hargreaves, Z. Samani, Estimating potential evapotranspiration. Journal of Irrigation and Drainage Engineering. ASCE, 108 (1982) 225-230.

      [15] J. V. Garcia, PrincipiosF’isicos de la Climatolog’ia. Ediciones UNALM (Universidad Nacional Agraria La Molina: Lima, Peru) (1994)

      [16] A. El-Sebaii, A. Trabea, Estimation of Global Solar Radiation on Horizontal Surfaces Over Egypt, Egypt. J. Solids, 28, 1 (2005) 163-175.

      [17] P. R. Bevington, Data reduction and error analysis for the physical sciences, first ed. McGraw Hill Book Co., New York (1969)

      [18] H. O. Merges, C. Ertekin, M. H. Sonmete, Evaluation of global solar radiation Models for Konya, Turkey. Energy Conversion and Management, 47 (2006) 3149-3173.

      [19] E. O. Ogolo, Evaluating the performance of some predictive models for estimating global solar radiation across varying climatic conditions in Nigeria. Indian Journal of Radio & space Physics, 39 (2010) 121-131.




Article ID: 29214
DOI: 10.14419/ijpr.v7i2.29214

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.