Prediction of direct normal irradiation using a new empirical sunshine duration-based model

Main Article Content

Abdelatif Takilalte
Ali Dali
Mohammed Laissaoui
Amar Bouhallassa


In this work, we are interested in presenting a new approach allowing us to express the Direct Normal solar Irradiation (DNI) according to the sunshine duration essentially. This choice is justified by the fact that in addition to the sunshine, duration has a strong correlation with solar irradiation, it is measured in many radiometric stations. Some clear sky models with modifications developed exclusively here are made valid for all types of sky. The proposed model is compared with one of the intelligent models such as the Support Vector Regression (SVR) for daily data from Ghardaïa.

Article Details

How to Cite
A. . Takilalte, A. . Dali, M. . Laissaoui, and A. . Bouhallassa, “Prediction of direct normal irradiation using a new empirical sunshine duration-based model”, J. Ren. Energies, vol. 26, no. 1, pp. 91 -, Jul. 2023.


P. Lauret, C. Voyant, T. Soubdhan, M. David, and P. Poggi, “A benchmarking of machine learning techniques for solar radiation forecasting in an insular context,” Sol. Energy, vol. 112, pp. 446–457, 2015, doi: 10.1016/j.solener.2014.12.014.

K. Mohammadi, S. Shamshirband, M. Hossein, K. Amjad, and D. Petkovic, “Support vector regression-based prediction of global solar radiation on a horizontal surface,” vol. 91, pp. 433–441, 2015, doi: 10.1016/j.enconman.2014.12.015.

E. W. Law, A. A. Prasad, M. Kay, and R. A. Taylor, “Direct normal irradiance forecasting and its application to concentrated solar thermal output forecasting - A review,” Sol. Energy, vol. 108, pp. 287–307, 2014, doi: 10.1016/j.solener.2014.07.008.

P. Ineichen, “Comparison and validation of three global-to-beam irradiance models against ground measurements,” Sol. Energy, vol. 82, no. 6, pp. 501–512, 2008, doi: 10.1016/j.solener.2007.12.006.

C. A. Gueymard, “A Simplified Clear Sky Model for Direct and Diffuse Insolation on Horizontal Surfaces,” Sol. Energy, vol. 82, no. 3, pp. 272–285, 2008, doi: 10.1016/j.solener.2007.04.008.

R. L. H. Richard E.Bird, simplified clear sky model for direct and diffuse insolation on horizontal surfaces. Goldon Colorado, USA: SERI/TR-642-761, Solar Energy Research Institute. 1981.

R. R. Perez, P. Ineichen, E. L. Maxwell, R. D. Seals, and A. Zelenka, “Dynamic global-to-direct irradiance conversion models,” ASHRAE Trans., vol. 98, no. pt 1, pp. 354–369, 1992.

B. Ridley, J. Boland, and P. Lauret, “Modelling of diffuse solar fraction with multiple predictors,” Renew. Energy, vol. 35, no. 2, pp. 478–483, 2010, doi: 10.1016/j.renene.2009.07.018.

M. S. Gul, T. Muneer, and H. D. Kambezidis, “Models for obtaining solar radiation from other meteorological data,” Sol. Energy, vol. 64, no. 1–3, pp. 99–108, 1998, doi: 10.1016/S0038-092X(98)00048-6.

R. Chen, E. Kang, X. Ji, J. Yang, and J. Wang, “An hourly solar radiation model under actual weather and terrain conditions: A case study in Heihe river basin,” Energy, vol. 32, no. 7, pp. 1148–1157, 2007, doi: 10.1016/

D. R. Myers, “General cloud cover modifier for clear sky solar radiation models,” Opt. Model. Meas. Sol. Energy Syst., vol. 6652, p. 665208, 2007, doi: 10.1117/12.732472.

F. J. K. Ideriah, “A model for calculating direct and diffuse solar radiation,” Sol. Energy, vol. 26, no. 5, pp. 447–452, 1981, doi: 10.1016/0038-092X(81)90224-3.

M. Iqbal, “Correlation of average diffuse and beam radiation with hours of bright sunshine,” Sol. Energy, vol. 23, no. 2, pp. 169–173, 1979, doi: 10.1016/0038-092X(79)90118-X.

J. Mubiru, “Using Artificial Neural Networks to Predict Direct Solar Irradiation,” Adv. Artif. Neural Syst., vol. 2011, pp. 1–6, 2011, doi: 10.1155/2011/142054.

T. khatib, A Mohamed and K. Sopian, A review of solar energy modeling techniques, vol. 16, no. 5. Elsevier Ltd, p. 2864-2869.

H. Suehrcke, R. S. Bowden, and K. G. T. Hollands, “Relationship between sunshine duration and solar radiation,” Sol. Energy, vol. 92, pp. 160–171, 2013, doi: 10.1016/j.solener.2013.02.026.

M.R. Yaïche et S.M.A. Bekkouche, “Conception et Validation d’un Programme Sous Excel pour l’Estimation du Rayonnement Solaire Direct en Algérie. Cas d’un Ciel Clair,” Rev. Int. d’Héliotechnique, vol. 39, pp. 50 – 55, 2009.

V. Vapnik, “The Nature of Statistical Learning Theory.” Springer-Verlag, New York, 1995.

V. Vapnik, S. E. Golowich, and A. Smola, “Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing,” Adv. Neural Inf. Process. Syst 9, pp. 281--287, 1997, doi: 10.1007/978-3-642-33311-8_5.

Z. Ramedani, M. Omid, A. Keyhani, B. Khoshnevisan, and H. Saboohi, “A comparative study between fuzzy linear regression and support vector regression for global solar radiation prediction in Iran,” Sol. Energy, vol. 109, no. 1, pp. 135–143, 2014, doi: 10.1016/j.solener.2014.08.023.

F. Girosi, “An equivalence between sparse approximation and support vector machines,” A.I. Memo No. 1606, MIT, vol. 1480, pp. 1455–1480, 1997.

S. Belaid and A. Mellit, “Prediction of daily and mean monthly global solar radiation using support vector machine in an arid climate,” ENERGY Convers. Manag., vol. 118, pp. 105–118, 2016, doi: 10.1016/j.enconman.2016.03.082.

R. Urraca, J. Antonanzas, M. Alia-Martinez, F. J. Martinez-De-Pison, and F. Antonanzas-Torres, “Smart baseline models for solar irradiation forecasting,” Energy Convers. Manag., vol. 108, pp. 539–548, 2016, doi: 10.1016/j.enconman.2015.11.033.

M. Zamo, O. Mestre, P. Arbogast, and O. Pannekoucke, “ScienceDirect A benchmark of statistical regression methods for short-term forecasting of photovoltaic electricity production, part I : Deterministic forecast of hourly production,” Sol. ENERGY, 2014, doi: 10.1016/j.solener.2013.12.006.

K. Mohammadi, S. Shamshirband, M. H. Anisi, K. Amjad Alam, and D. Petkovic, “Support vector regression based prediction of global solar radiation on a horizontal surface,” Energy Convers. Manag., vol. 91, pp. 433–441, 2015, doi: 10.1016/j.enconman.2014.12.015.

L. Martin, L. F. Zarzalejo, J. Polo, A. Navarro, R. Marchante, and M. Cony, “Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning,” Sol. Energy, vol. 84, no. 10, pp. 1772–1781, 2010, doi: 10.1016/j.solener.2010.07.002.

K. Dahmani, R. Dizene, G. Notton, C. Paoli, C. Voyant, and M. L. Nivet, “Estimation of 5-min time-step data of tilted solar global irradiation using ANN (Artificial Neural Network) model,” Energy, vol. 70, pp. 374–381, 2014, doi: 10.1016/

A. Takilalte, S. Harrouni, M. R. Yaiche, and L. Mora-Lopez, “New approach to estimate 5-min global solar irradiation data on tilted planes from horizontal measurement,” Renew. Energy, vol. 145, pp. 2477–2488, 2020, doi: 10.1016/j.renene.2019.07.165.

R. L. H. Richard E.Bird, simplified clear sky model for direct and diffuse insolation on horizontal surfaces. Goldon Colorado, USA: SERI/TR-642-761, Solar Energy Research Institute. 1981.

Muhammad Iqbal, An Introduction to Solar Radiation. New York - London: Academic Press, 1983.

A. Takilalte, S. Harrouni, and J. Mora, “Forecasting global solar irradiance for various resolutions using time series models - case study: Algeria,” Energy Sources, Part A Recover. Util. Environ. Eff., vol. 44, no. 1, pp. 1–20, 2022, doi: 10.1080/15567036.2019.1649756.