IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v47y2012icp38-44.html
   My bibliography  Save this article

Estimating global solar radiation using common meteorological data in Akure, Nigeria

Author

Listed:
  • Adaramola, Muyiwa S.

Abstract

In this study, the global solar radiation on horizontal surface in Akure, Nigeria (Latitude 7.25° N and Longitude 5.2° E) using 22-year data (July 1983–June 2005) was analysed. Simple empirical correlations for evaluating the monthly average daily global solar radiation were developed. The calculated monthly clearness index values indicates that prevailing weather condition in Akure is partly overcast but can become heavily overcast during the months of July–September. The Angstrom–Page correlation predicted the monthly average daily global solar radiation better than the other correlations developed in this study. However, in the absence of the sunshine hour data, it was found that temperature only based correlations (especially the average temperature based correlation) and precipitation based correlation can be used to predict the global solar radiation within reasonable level of accuracy in Akure. The correlations presented in this study could be applied to locations with comparable weather condition to Akure.

Suggested Citation

  • Adaramola, Muyiwa S., 2012. "Estimating global solar radiation using common meteorological data in Akure, Nigeria," Renewable Energy, Elsevier, vol. 47(C), pages 38-44.
    • Handle: RePEc:eee:renene:v:47:y:2012:i:c:p:38-44
    DOI: 10.1016/j.renene.2012.04.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148112002467
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2012.04.005?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.

    References listed on IDEAS

    as
    1. Almorox, J. & Hontoria, C. & Benito, M., 2011. "Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain)," Applied Energy, Elsevier, vol. 88(5), pages 1703-1709, May.
    2. Gopinathan, K.K. & Soler, Alfonso, 1992. "A sunshine dependent global insolation model for latitudes between 60°N and 70°N," Renewable Energy, Elsevier, vol. 2(4), pages 401-404.
    3. Yohanna, Jonathan K. & Itodo, Isaac N. & Umogbai, Victor I., 2011. "A model for determining the global solar radiation for Makurdi, Nigeria," Renewable Energy, Elsevier, vol. 36(7), pages 1989-1992.
    4. Chineke, Theo Chidiezie, 2008. "Equations for estimating global solar radiation in data sparse regions," Renewable Energy, Elsevier, vol. 33(4), pages 827-831.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giwa, Adewale & Alabi, Adetunji & Yusuf, Ahmed & Olukan, Tuza, 2017. "A comprehensive review on biomass and solar energy for sustainable energy generation in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 620-641.
    2. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
    3. Dos Santos, Cícero Manoel & De Souza, José Leonaldo & Ferreira Junior, Ricardo Araujo & Tiba, Chigueru & de Melo, Rinaldo Oliveira & Lyra, Gustavo Bastos & Teodoro, Iêdo & Lyra, Guilherme Bastos & Lem, 2014. "On modeling global solar irradiation using air temperature for Alagoas State, Northeastern Brazil," Energy, Elsevier, vol. 71(C), pages 388-398.
    4. Bayrakçı, Hilmi Cenk & Demircan, Cihan & Keçebaş, Ali, 2018. "The development of empirical models for estimating global solar radiation on horizontal surface: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2771-2782.
    5. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2015. "Review and statistical analysis of different global solar radiation sunshine models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1869-1880.
    6. Makade, Rahul G. & Jamil, Basharat, 2018. "Statistical analysis of sunshine based global solar radiation (GSR) models for tropical wet and dry climatic Region in Nagpur, India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 22-43.
    7. Khatib, Tamer & Mohamed, Azah & Sopian, K., 2012. "A review of solar energy modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2864-2869.
    8. Khalil, Samy A. & Shaffie, A.M., 2013. "A comparative study of total, direct and diffuse solar irradiance by using different models on horizontal and inclined surfaces for Cairo, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 853-863.
    9. Amrouche, Badia & Le Pivert, Xavier, 2014. "Artificial neural network based daily local forecasting for global solar radiation," Applied Energy, Elsevier, vol. 130(C), pages 333-341.
    10. Halabi, Laith M. & Mekhilef, Saad & Hossain, Monowar, 2018. "Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation," Applied Energy, Elsevier, vol. 213(C), pages 247-261.
    11. Besharat, Fariba & Dehghan, Ali A. & Faghih, Ahmad R., 2013. "Empirical models for estimating global solar radiation: A review and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 798-821.
    12. Flores, Juan J. & Graff, Mario & Rodriguez, Hector, 2012. "Evolutive design of ARMA and ANN models for time series forecasting," Renewable Energy, Elsevier, vol. 44(C), pages 225-230.
    13. Mecibah, Mohamed Salah & Boukelia, Taqiy Eddine & Tahtah, Reda & Gairaa, Kacem, 2014. "Introducing the best model for estimation the monthly mean daily global solar radiation on a horizontal surface (Case study: Algeria)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 194-202.
    14. El Mghouchi, Y. & Ajzoul, T. & El Bouardi, A., 2016. "Prediction of daily solar radiation intensity by day of the year in twenty-four cities of Morocco," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 823-831.
    15. Bakirci, Kadir, 2009. "Correlations for estimation of daily global solar radiation with hours of bright sunshine in Turkey," Energy, Elsevier, vol. 34(4), pages 485-501.
    16. Jose Manuel Barrera & Alejandro Reina & Alejandro Maté & Juan Carlos Trujillo, 2020. "Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    17. Das, Aparna & Paul, Saikat Kumar, 2015. "Artificial illumination during daytime in residential buildings: Factors, energy implications and future predictions," Applied Energy, Elsevier, vol. 158(C), pages 65-85.
    18. Ajayi, Oluseyi O, 2013. "Sustainable energy development and environmental protection: Implication for selected states in West Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 532-539.
    19. El Mghouchi, Y. & Ajzoul, T. & Taoukil, D. & El Bouardi, A., 2016. "The most suitable prediction model of the solar intensity, on horizontal plane, at various weather conditions in a specified location in Morocco," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 84-98.
    20. Hassan, Gasser E. & Youssef, M. Elsayed & Mohamed, Zahraa E. & Ali, Mohamed A. & Hanafy, Ahmed A., 2016. "New Temperature-based Models for Predicting Global Solar Radiation," Applied Energy, Elsevier, vol. 179(C), pages 437-450.

    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:renene:v:47:y:2012:i:c:p:38-44. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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/renewable-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.