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Evaluation of overcast-sky luminance models against measured Hong Kong data

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  • Li, Danny H. W.
  • Lau, Chris C. S.
  • Lam, Joseph C.

Abstract

Sky luminance distribution is one of the most important quantities for predicting indoor daylight illuminance levels. Overcast-sky types are essential because they are used in more general sky models and appear quite frequent in some places. This paper presents the work on the evaluation of six worldwide overcast-sky models against two-year (1999-2000) measured Hong Kong sky luminance data. Overcast-sky conditions were identified using cloud cover (CLD) and a subsequent interpretation the overcast skies into thin and heavy overcast types was conducted in conjunction with the clearness index (Kt). A statistical analysis of the models has indicated that the International Commission on Illumination (CIE) standard overcast sky model performed the best, in particular for the heavy overcast-sky condition. The Building Research Establishment (BRE) quasi-overcast-sky model showed a good agreement with the thin overcast distributions which may include a circumstance component and the sky luminance patterns being orientation dependent.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:70:y:2001:i:4:p:321-331
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    References listed on IDEAS

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    1. Li, Danny H.W & Lam, Joseph C, 2000. "Measurements of solar radiation and illuminance on vertical surfaces and daylighting implications," Renewable Energy, Elsevier, vol. 20(4), pages 389-404.
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    Cited by:

    1. Acosta, Ignacio & Navarro, Jaime & Sendra, Juan José, 2014. "Lighting design in courtyards: Predictive method of daylight factors under overcast sky conditions," Renewable Energy, Elsevier, vol. 71(C), pages 243-254.
    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. & Lou, Siwei, 2018. "Review of solar irradiance and daylight illuminance modeling and sky classification," Renewable Energy, Elsevier, vol. 126(C), pages 445-453.
    4. 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.
    5. Li, Danny H.W., 2010. "A review of daylight illuminance determinations and energy implications," Applied Energy, Elsevier, vol. 87(7), pages 2109-2118, July.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.

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