IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v15y1990i5p395-402.html
   My bibliography  Save this article

Hourly solar radiation over Bahrain

Author

Listed:
  • Al-Sadah, Fayez H
  • Ragab, Farouk M
  • Arshad, Mirza K

Abstract

An empirical formula for estimating hourly solar radiation has been developed. The average hourly total solar radiation has been computed as a function of local time. The results compare well with experimental data measured at latitude Ø = 26 °N. There is also good agreement between our model and that of other authors.

Suggested Citation

  • Al-Sadah, Fayez H & Ragab, Farouk M & Arshad, Mirza K, 1990. "Hourly solar radiation over Bahrain," Energy, Elsevier, vol. 15(5), pages 395-402.
  • Handle: RePEc:eee:energy:v:15:y:1990:i:5:p:395-402
    DOI: 10.1016/0360-5442(90)90036-2
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0360544290900362
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/0360-5442(90)90036-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Dazhi & Gu, Chaojun & Dong, Zibo & Jirutitijaroen, Panida & Chen, Nan & Walsh, Wilfred M., 2013. "Solar irradiance forecasting using spatial-temporal covariance structures and time-forward kriging," Renewable Energy, Elsevier, vol. 60(C), pages 235-245.
    2. Hanany Tolba & Nouha Dkhili & Julien Nou & Julien Eynard & Stéphane Thil & Stéphane Grieu, 2020. "Multi-Horizon Forecasting of Global Horizontal Irradiance Using Online Gaussian Process Regression: A Kernel Study," Energies, MDPI, vol. 13(16), pages 1-23, August.
    3. Trapero, Juan R., 2016. "Calculation of solar irradiation prediction intervals combining volatility and kernel density estimates," Energy, Elsevier, vol. 114(C), pages 266-274.
    4. Dong, Zibo & Yang, Dazhi & Reindl, Thomas & Walsh, Wilfred M., 2013. "Short-term solar irradiance forecasting using exponential smoothing state space model," Energy, Elsevier, vol. 55(C), pages 1104-1113.
    5. Trapero, Juan R. & Kourentzes, Nikolaos & Martin, A., 2015. "Short-term solar irradiation forecasting based on Dynamic Harmonic Regression," Energy, Elsevier, vol. 84(C), pages 289-295.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:15:y:1990:i:5:p:395-402. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.