Experimental Prediction of Hourly Diffuse Solar Radiation with Clearness Index in Baghdad (Iraq)

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Hussein M. Taqi Al-Najjar, Akram A. Abbood Al-Khazzar

Hussein Taqi M Al-Najjar and Akram Abbood A Al-Khazzar. Experimental Prediction of Hourly Diffuse Solar Radiation with Clearness Index in Baghdad (Iraq). International Journal of Computer Applications 158(7):20-28, January 2017. BibTeX

	author = {Hussein M. Taqi Al-Najjar and Akram A. Abbood Al-Khazzar},
	title = {Experimental Prediction of Hourly Diffuse Solar Radiation with Clearness Index in Baghdad (Iraq)},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2017},
	volume = {158},
	number = {7},
	month = {Jan},
	year = {2017},
	issn = {0975-8887},
	pages = {20-28},
	numpages = {9},
	url = {http://www.ijcaonline.org/archives/volume158/number7/26921-2017912849},
	doi = {10.5120/ijca2017912849},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Design and simulation of solar energy installations need hourly data of diffuse and beam radiation components for assessing the dynamic behavior of those systems. However, the most widely available data is the global solar radiation. Whereas, diffuse and beam data are not readily affordable. Thus, numerous empirical models of correlations were developed at different sites in the world to predict the required radiation components. In the present paper, an hourly correlation expressed in a third-degree polynomial relating the diffuse fraction with the clearness index was developed based on field measurements of global and diffuse solar radiations in Baghdad city (33.33o N), Iraq. The validation and accuracy of the developed correlation was evaluated using six widely used statistical parameters. Among these parameters, the values of linear coefficient of correlation, mean percentage error and root mean square error were found to be 0.885, 6.24% and 8.0% respectively which indicates good performance. In addition, eight different empirical diffuse models for various sites were chosen from the literature for statistical comparison with the developed correlation in this study. The best model was that of South America at site latitude 23.56o S with mean percentage error 16% and root mean square error 11.5% which shows the largest agreement. A computer program was established for generating the necessary data for developing the required correlation and also for calculating the essential statistical evaluations and comparisons in the present work.


  1. Panwar, N.L., Kaushik, S.C. and Kothari, S. Role of renewable energy sources in environmental protection: a review. Renewable and Sustainable Energy Reviews, 15(3):1513-1524, 2011.
  2. Hernandez, R.R., Easter, S.B., Murphy-Mariscal, M.L., Maestre, F.T., Tavassoli, M., Allen, E.B., Barrows, C.W., Belnap, J., Ochoa-Hueso, R., Ravi, S. and Allen, M.F. Environmental impacts of utility-scale solar energy. Renewable and Sustainable Energy Reviews, 29:766-779, 2014.
  3. Mekhilef, S., Saidur, R. and Safari, A. A review on solar energy use in industries. Renewable and Sustainable Energy Reviews, 15(4):1777-1790, 2011.
  4. Eicker, U. Solar Technologies for Buildings. John Wiley & Sons, 2006.
  5. Al-Najjar, H. M. T. Electric, heating and cooling yields of solar collectors for different atmospheric conditions and tilt angles. International Journal of Computer Applications, 141(10):1-10, May 2016.
  6. Bakirci, K. Models for the estimation of diffuse solar radiation for typical cities in Turkey. Energy, 82:827-838, 2015.
  7. Liu, B.Y. and Jordan, R.C. The interrelationship and characteristic distribution of direct, diffuse and total solar radiation. Solar Energy, 4(3):1-19, 1960.
  8. Wong, L.T. and Chow, W.K. Solar radiation model. Applied Energy, 69 (3):191-224, 2001.
  9. Khorasanizadeh, H. and Mohammadi, K. Diffuse solar radiation on a horizontal surface: Reviewing and categorizing the empirical models. Renewable and Sustainable Energy Reviews, 53:338-362, 2016.
  10. Boland, J., Scott, L. and Luther, M. Modeling the diffuse fraction of global solar radiation on a horizontal surface. Environmetrics, 12:103-116, 2001.
  11. Orgill, J.F. and Hollands, K.G.T. Correlation equation for hourly diffuse radiation on a horizontal surface. Solar Energy, 19:357-359, 1977.
  12. Erbs, D.G., Klein, S.A. and Duffie, J.A. Estimation of the diffuse radiation fraction for hourly, daily and monthly average global radiation. Solar Energy, 28(4): 293-302, 1982.
  13. Reindl, D.T., Beckman, W.A. and Duffie, J.A. Diffuse fraction correlations. Solar Energy, 45(1):1-7, 1990.
  14. Karatasou, S., Santamouris, M. and Geros, V. Analysis of experimental data on diffuse solar radiation in Athens, Greece, for building applications. International Journal of Sustainable Energy, 23:1-11, 2003.
  15. Chandrasekaran, J. and Kumar, S. Hourly diffuse fraction correlation at a tropical location. Solar Energy, 53(6):505-510, 1994.
  16. Lam, J.C. and Li, D.H. Correlation between global solar radiation and its direct and diffuse components. Building and Environment, 31(6):527-535, 1996.
  17. De Miguel, A., Bilbao, J., Aguiar, R., Kambezidis, H. and Negro, E. Diffuse solar irradiation model evaluation in the north Mediterranean belt area. Solar Energy, 70(2):143-153, 2001.
  18. Hawlader, M.N.A. Diffuse, global and extra-terrestrial solar radiation for Singapore. International Journal of Ambient Energy, 5(1):31-38, 1984.
  19. Oliveira, A.P., Escobedo, J.F., Machado, A.J. and Soares, J. Correlation models of diffuse solar-radiation applied to the city of Sao Paulo, Brazil. Applied Energy, 71:59-73, 2002.
  20. Soares, J., Oliveira, A.P., Božnar, M.Z., Mlakar, P., Escobedo, J.F. and Machado, A.J. Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique. Applied Energy, 79(2):201-214, 2004.
  21. Jacovides, C.P., Tymvios, F.S., Assimakopoulos, V.D. and Kaltsounides, N.A. Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation. Renewable Energy, 31(15):2492-2504, 2006.
  22. Duffie, J.A., Beckman, W.A. Solar Engineering of Thermal Processes. John Wiley & Sons, 2006.
  23. Iqbal, M. An Introduction to Solar Radiation. Elsevier, 2012.
  24. Robinson, N. and Stoch, L. Sky radiation measurement and corrections. Journal of Applied Meteorology, 3(2):179-181, 1964.
  25. Steven, M.D. and Unsworth, M.H. Shade‐ring corrections for pyranometer measurements of diffuse solar radiation from cloudless skies. Quarterly Journal of the Royal Meteorological Society, 106(450):865-872, 1980.
  26. Stanhill, G. Observations of shade‐ring corrections for diffuse sky radiation measurements at the Dead Sea. Quarterly Journal of the Royal Meteorological Society, 111(470):1125-1130, 1985.
  27. Ineichen, P., Gremaud, J.M., Guisan, O. and Mermoud, A. Study of the corrective factor involved when measuring the diffuse solar radiation by use of the ring method. Solar Energy, 31(1):113-117, 1983.
  28. Batlles, F.J., Olmo, F.J. and Alados-Arboledas, L. On shadow band correction methods for diffuse irradiance measurements. Solar Energy, 54(2):105-114, 1995.
  29. De Oliveira, A.P., Machado, A.J. and Escobedo, J.F. A new shadow-ring device for measuring diffuse solar radiation at the surface. Journal of Atmospheric and Oceanic Technology, 19(5):698-708, 2002.
  30. http://renewable.eastwestin.com/solar/sensors/shadow-band.php.
  31. Coulson, K. Solar and Terrestrial Radiation: Methods and Measurements. Elsevier, 2012.
  32. Walpole, R.E., Myers, R.H., Myers, S.L. and Ye, K. Probability and Statistics for Engineers and Scientists. (Vol. 5). Macmillan, 1993.


hourly diffuse fraction, clearness index, empirical models, statistical parameters, Baghdad (Iraq).