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Development and evaluation of empirical models for the estimation of hourly horizontal diffuse solar irradiance in the United Kingdom

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  • Nunez Munoz, Maria
  • Ballantyne, Erica E.F.
  • Stone, David A.

Abstract

Solar irradiation data is required in many applications to obtain the solar energy output. However, solar irradiation data is not always available, especially horizontal surface diffuse solar irradiation. This has led to the creation of empirical solar models to predict these values. The aim of this paper is to develop an empirical model for the estimation of hourly diffuse solar irradiance on horizontal surfaces. Initially, a set of existing empirical models have been evaluated to test their accuracy. New models have been developed based on ground level measurements of global and diffuse horizontal solar irradiation that have been obtained from three different regions of the United Kingdom: South Yorkshire, Norfolk, and West Sussex for a period between 1982 and 1999. The models created for each region correlate the diffuse fraction (kd) and the clearness index (kt), for the estimation of hourly diffuse solar irradiance on horizontal surfaces. The models developed for the three regions were evaluated to test their accuracy using error histograms and by contrasting different datasets. Finally, a comparison of the new models to the existing empirical models showed that the new developed correlations significantly improved the existing empirical models for the three regions evaluated in this study.

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  • Nunez Munoz, Maria & Ballantyne, Erica E.F. & Stone, David A., 2022. "Development and evaluation of empirical models for the estimation of hourly horizontal diffuse solar irradiance in the United Kingdom," Energy, Elsevier, vol. 241(C).
    • Handle: RePEc:eee:energy:v:241:y:2022:i:c:s0360544221030693
    DOI: 10.1016/j.energy.2021.122820
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    Cited by:

    1. Yin, Kaili & Zhang, Xiaojing & Xie, Jingchao & Hao, Ziyang & Xiao, Guofeng & Liu, Jiaping, 2023. "Modeling hourly solar diffuse fraction on a horizontal surface based on sky conditions clustering," Energy, Elsevier, vol. 272(C).
    2. Maria Nunez Munoz & Erica E. F. Ballantyne & David A. Stone, 2023. "Assessing the Economic Impact of Introducing Localised PV Solar Energy Generation and Energy Storage for Fleet Electrification," Energies, MDPI, vol. 16(8), pages 1-27, April.
    3. Mohamed A. Ali & Ashraf Elsayed & Islam Elkabani & Mohammad Akrami & M. Elsayed Youssef & Gasser E. Hassan, 2023. "Optimizing Artificial Neural Networks for the Accurate Prediction of Global Solar Radiation: A Performance Comparison with Conventional Methods," Energies, MDPI, vol. 16(17), pages 1-30, August.

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