On a universal model for the prediction of the daily global solar radiation

被引:27
|
作者
Kaplanis, S. [1 ]
Kumar, Jatin [1 ]
Kaplani, E. [1 ,2 ]
机构
[1] Technol Educ Inst Western Greece, Dept Mech Engn, Meg Alexandrou 1, Patras 26334, Greece
[2] Univ E Anglia, Sch Math, Norwich NR4 7TJ, Norfolk, England
关键词
Daily solar radiation; Universal model; Prediction; PERFORMANCE; SUNSHINE;
D O I
10.1016/j.renene.2016.01.037
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A model to predict the mean expected daily global solar radiation, H(n) on a day n, at a site with latitude phi is proposed. The model is based on two cosine functions. A regression analysis taking into account the mean measured values H-m.meas(n) obtained from SoDa database for 42 sites in the Northern Hemisphere resulted in a set of mathematical expressions of split form to predict H(n). The parameters of the two cosine model for 0 degrees < phi < 23 degrees are obtained by regression analysis using a sum of 3-8 Gaussian functions, while for 23 degrees < phi < 71 degrees the two cosine model parameters are expressed by a sum of exponential functions or the product of an exponential and a cosine function. The main equation of the model and the set of parametric expressions provide H(n) for any phi on Earth. Validation results of this model are provided along with the statistical estimators NMBE, NRMSE and t-statistic in comparison to the corresponding values from three databases of NASA, SoDa and the measured values from ground stations provided in Meteonorm. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:178 / 188
页数:11
相关论文
共 50 条
  • [1] Model selection for accurate daily global solar radiation prediction in China
    Gouda, Shaban G.
    Hussein, Zakia
    Luo, Shuai
    Yuan, Qiaoxia
    [J]. JOURNAL OF CLEANER PRODUCTION, 2019, 221 : 132 - 144
  • [2] An Interpretable Machine Learning Model for Daily Global Solar Radiation Prediction
    Chaibi, Mohamed
    Benghoulam, El Mahjoub
    Tarik, Lhoussaine
    Berrada, Mohamed
    El Hmaidi, Abdellah
    [J]. ENERGIES, 2021, 14 (21)
  • [3] Development of a hybrid computational intelligent model for daily global solar radiation prediction
    Goliatt, Leonardo
    Yaseen, Zaher Mundher
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2023, 212
  • [4] Artificial neural network based prediction model of daily global solar radiation in Morocco
    Mejdoul, R.
    Taqi, M.
    Belouaggadia, N.
    [J]. JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2013, 5 (06)
  • [5] Prediction of daily global solar radiation using fuzzy systems
    Iqdour, R.
    Zeroual, A.
    [J]. INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY, 2007, 26 (01) : 19 - 29
  • [6] A spatiotemporal universal model for the prediction of the global solar radiation based on Fourier series and the site altitude
    Kaplani, E.
    Kaplanis, S.
    Mondal, S.
    [J]. RENEWABLE ENERGY, 2018, 126 : 933 - 942
  • [7] SARIMA-SVM Hybrid Model for the Prediction of Daily Global Solar Radiation Time Series
    Boualit, Sabrina Belaid
    Mellit, Adel
    [J]. PROCEEDINGS OF 2016 INTERNATIONAL RENEWABLE & SUSTAINABLE ENERGY CONFERENCE (IRSEC' 16), 2016, : 712 - +
  • [8] ANN Based Prediction of Daily Global Solar Radiation for Photovoltaics Applications
    Yadav, Amit Kumar
    Malik, Hasmat
    Chandel, S. S.
    [J]. 2015 ANNUAL IEEE INDIA CONFERENCE (INDICON), 2015,
  • [9] Prediction of global daily solar radiation using higher order statistics
    Safi, S
    Zeroual, A
    Hassani, M
    [J]. RENEWABLE ENERGY, 2002, 27 (04) : 647 - 666
  • [10] A rule based fuzzy model for the prediction of daily solar radiation
    Iqdour, R
    Zeroual, A
    [J]. 2004 IEEE International Conference on Industrial Technology (ICIT), Vols. 1- 3, 2004, : 1482 - 1487