IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v31y2014icp563-574.html
   My bibliography  Save this article

A review of the CIE general sky classification approaches

Author

Listed:
  • Li, Danny H.W.
  • Chau, T.C.
  • Wan, Kevin K.W.

Abstract

Recently, the International Commission on Illumination (CIE) has adopted a range of 15 standard sky distributions representing the whole probable spectrum of actual skies in the world. Each sky standard has its own well-defined sky luminance pattern which can be conveniently used to calculate the sky radiance and luminance for a given sky patch and the solar irradiance and daylight illuminance on inclined surfaces facing various orientations. The crucial issues are whether the skies could be correctly identified. This paper presents the work on the classification of the CIE Standard General Skies using various climatic parameters and indices. Meteorological variables namely luminance distribution for the whole sky including zenith luminance, global, direct-beam and sky-diffuse illuminance on a horizontal surface and vertical sky illuminance, and horizontal and vertical solar irradiance data are adopted for analysis. The results demonstrate that there are a number of appropriate climatic parameters for sky classification and the selection depends on their availability, accuracy and sensitivity. The approaches could contribute to the estimation of solar irradiance and daylight illuminance which are essential to the renewable and sustainable developments and energy-efficient building designs.

Suggested Citation

  • Li, Danny H.W. & Chau, T.C. & Wan, Kevin K.W., 2014. "A review of the CIE general sky classification approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 563-574.
    • Handle: RePEc:eee:rensus:v:31:y:2014:i:c:p:563-574
    DOI: 10.1016/j.rser.2013.12.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032113008320
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2013.12.018?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. Kittler, R. & Darula, S., 2002. "Parametric definition of the daylight climate," Renewable Energy, Elsevier, vol. 26(2), pages 177-187.
    2. Markou, M.T. & Kambezidis, H.D. & Bartzokas, A. & Katsoulis, B.D. & Muneer, T., 2005. "Sky type classification in Central England during winter," Energy, Elsevier, vol. 30(9), pages 1667-1674.
    3. Quesada, Guillermo & Rousse, Daniel & Dutil, Yvan & Badache, Messaoud & Hallé, Stéphane, 2012. "A comprehensive review of solar facades. Transparent and translucent solar facades," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2643-2651.
    4. Singh, M.C. & Garg, S.N., 2010. "Illuminance estimation and daylighting energy savings for Indian regions," Renewable Energy, Elsevier, vol. 35(3), pages 703-711.
    5. Ma, Zhenjun & Wang, Shengwei, 2009. "Building energy research in Hong Kong: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1870-1883, October.
    6. Serra, Rafael, 1998. "Chapter 6--Daylighting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 2(1-2), pages 115-155, June.
    7. Chirarattananon, Surapong & Chaiwiwatworakul, Pipat, 2007. "Distributions of sky luminance and radiance of North Bangkok under standard distributions," Renewable Energy, Elsevier, vol. 32(8), pages 1328-1345.
    8. Li, Danny H.W. & Lau, Chris C.S. & Lam, Joseph C., 2005. "Predicting daylight illuminance on inclined surfaces using sky luminance data," Energy, Elsevier, vol. 30(9), pages 1649-1665.
    9. Janjai, Serm & Plaon, Piyanuch, 2011. "Estimation of sky luminance in the tropics using artificial neural networks: Modeling and performance comparison with the CIE model," Applied Energy, Elsevier, vol. 88(3), pages 840-847, March.
    10. Younes, S. & Muneer, T., 2007. "Clear-sky classification procedures and models using a world-wide data-base," Applied Energy, Elsevier, vol. 84(6), pages 623-645, June.
    11. Li, Danny H.W. & Chau, Natalie T.C. & Wan, Kevin K.W., 2013. "Predicting daylight illuminance and solar irradiance on vertical surfaces based on classified standard skies," Energy, Elsevier, vol. 53(C), pages 252-258.
    12. Li, Danny H. W. & Lau, Chris C. S. & Lam, Joseph C., 2001. "Evaluation of overcast-sky luminance models against measured Hong Kong data," Applied Energy, Elsevier, vol. 70(4), pages 321-331, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Khalid Alshaibani & Danny Li & Emmanuel Aghimien, 2020. "Sky Luminance Distribution Models: A Comparison with Measurements from a Maritime Desert Region," Energies, MDPI, vol. 13(20), pages 1-12, October.
    2. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C., 2017. "CIE Standard Sky classification by accessible climatic indices," Renewable Energy, Elsevier, vol. 113(C), pages 347-356.
    3. Li, Danny H.W. & Lou, Siwei & Lam, Joseph C. & Wu, Ronald H.T., 2016. "Determining solar irradiance on inclined planes from classified CIE (International Commission on Illumination) standard skies," Energy, Elsevier, vol. 101(C), pages 462-470.
    4. Lou, Siwei & Li, Danny.H.W. & Chen, Wenqiang, 2019. "Identifying overcast, partly cloudy and clear skies by illuminance fluctuations," Renewable Energy, Elsevier, vol. 138(C), pages 198-211.
    5. Ramírez-Faz, J. & López-Luque, R. & Casares, F.J., 2015. "Development of synthetic hemispheric projections suitable for assessing the sky view factor on vertical planes," Renewable Energy, Elsevier, vol. 74(C), pages 279-286.
    6. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.

    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. Li, Danny H.W. & Lou, Siwei, 2018. "Review of solar irradiance and daylight illuminance modeling and sky classification," Renewable Energy, Elsevier, vol. 126(C), pages 445-453.
    2. Mettanant, Vichuda & Chaiwiwatworakul, Pipat & Chirarattananon, Surapong, 2017. "A model of Thai’s sky luminance distribution based on reduced CIE standard sky types," Renewable Energy, Elsevier, vol. 103(C), pages 739-749.
    3. Li, Danny H.W., 2010. "A review of daylight illuminance determinations and energy implications," Applied Energy, Elsevier, vol. 87(7), pages 2109-2118, July.
    4. Mavromatidis, Lazaros Elias & Marsault, Xavier & Lequay, Hervé, 2014. "Daylight factor estimation at an early design stage to reduce buildings' energy consumption due to artificial lighting: A numerical approach based on Doehlert and Box–Behnken designs," Energy, Elsevier, vol. 65(C), pages 488-502.
    5. Li, Danny H.W. & Lou, Siwei & Lam, Joseph C. & Wu, Ronald H.T., 2016. "Determining solar irradiance on inclined planes from classified CIE (International Commission on Illumination) standard skies," Energy, Elsevier, vol. 101(C), pages 462-470.
    6. Li, Danny H.W. & Chau, Natalie T.C. & Wan, Kevin K.W., 2013. "Predicting daylight illuminance and solar irradiance on vertical surfaces based on classified standard skies," Energy, Elsevier, vol. 53(C), pages 252-258.
    7. Su-In Yun & Kang-Soo Kim, 2018. "Sky Luminance Measurements Using CCD Camera and Comparisons with Calculation Models for Predicting Indoor Illuminance," Sustainability, MDPI, vol. 10(5), pages 1-29, May.
    8. 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.
    9. Lou, Siwei & Huang, Yu & Li, Danny H.W. & Xia, Dawei & Zhou, Xiaoqing & Zhao, Yang, 2020. "A novel method for fast sky conditions identification from global solar radiation measurements," Renewable Energy, Elsevier, vol. 161(C), pages 77-90.
    10. Janjai, Serm & Plaon, Piyanuch, 2011. "Estimation of sky luminance in the tropics using artificial neural networks: Modeling and performance comparison with the CIE model," Applied Energy, Elsevier, vol. 88(3), pages 840-847, March.
    11. Ferraro, V. & Mele, M. & Marinelli, V., 2012. "Analysis of sky luminance experimental data and comparison with calculation methods," Energy, Elsevier, vol. 37(1), pages 287-298.
    12. De Rosa, A. & Ferraro, V. & Kaliakatsos, D. & Marinelli, V., 2010. "Calculating indoor natural illuminance in overcast sky conditions," Applied Energy, Elsevier, vol. 87(3), pages 806-813, March.
    13. Ferraro, V. & Igawa, N. & Marinelli, V., 2010. "INLUX-DBR – A calculation code to calculate indoor natural illuminance inside buildings under various sky conditions," Energy, Elsevier, vol. 35(9), pages 3722-3730.
    14. Li, Danny H.W. & Lam, Tony N.T. & Cheung, K.L. & Tang, H.L., 2008. "An analysis of luminous efficacies under the CIE standard skies," Renewable Energy, Elsevier, vol. 33(11), pages 2357-2365.
    15. Barbosa, Sabrina & Ip, Kenneth, 2014. "Perspectives of double skin façades for naturally ventilated buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 1019-1029.
    16. Li, Danny H.W. & Lam, Tony N.T. & Chan, Wilco W.H. & Mak, Ada H.L., 2009. "Energy and cost analysis of semi-transparent photovoltaic in office buildings," Applied Energy, Elsevier, vol. 86(5), pages 722-729, May.
    17. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C., 2017. "CIE Standard Sky classification by accessible climatic indices," Renewable Energy, Elsevier, vol. 113(C), pages 347-356.
    18. Benkaciali, Saïd & Haddadi, Mourad & Khellaf, Abdellah, 2018. "Evaluation of direct solar irradiance from 18 broadband parametric models: Case of Algeria," Renewable Energy, Elsevier, vol. 125(C), pages 694-711.
    19. Chi, Fang'ai & Zhang, Jianxun & Li, Gaomei & Zhu, Zongzhou & Bart, Dewancker, 2019. "An investigation of the impact of Building Azimuth on energy consumption in sizhai traditional dwellings," Energy, Elsevier, vol. 180(C), pages 594-614.
    20. Ma, Tao & Østergaard, Poul Alberg & Lund, Henrik & Yang, Hongxing & Lu, Lin, 2014. "An energy system model for Hong Kong in 2020," Energy, Elsevier, vol. 68(C), pages 301-310.

    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:rensus:v:31:y:2014:i:c:p:563-574. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.