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A study of the skylight coverage ratio for air-conditioned atriumsin the hot and humid regions

Author

Listed:
  • Siwei Lou
  • Yu Huang
  • Dawei Xia
  • Isaac Y F Lun
  • Danny H W Li

Abstract

The skylight on the roof of an atrium can be popular for commercial malls to illuminate the core area of the building. However, the solar radiation and its heat can get into the building together with the daylight, causing excessive cooling load. This paper studies the daylighting and energy performances of skylight coverage area for the air-conditioned atriums in the hot and humid regions. The energy performance with different atrium heights, glass types and the coverage ratios of the skylight are studied. The daylight performance was simulated by the ray-tracing Radiance and was transferred into EnergyPlus for energy evaluations. The finding suggested that, for hot and humid climates, the skylight coverage ratio should be controlled carefully to prevent the excessive solar heat gain. When the on/off lighting control is applied, the total energy consumption of the single-floor cases (or of the top floor for the multi-floor cases) leveled off when the coverage ratio of the skylight reached 9%. Thus, the skylight is favorable to the energy saving of the low-rise or single-floor commercial buildings only under the current assumptions, as the ground of the atrium cannot be well illuminated while the excessive solar radiation gets into the building. The skylight should be shaded in cooling seasons to prevent the excessive solar heat gains.

Suggested Citation

  • Siwei Lou & Yu Huang & Dawei Xia & Isaac Y F Lun & Danny H W Li, 2021. "A study of the skylight coverage ratio for air-conditioned atriumsin the hot and humid regions," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 16(3), pages 946-955.
  • Handle: RePEc:oup:ijlctc:v:16:y:2021:i:3:p:946-955.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctab023
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    Cited by:

    1. Li, Danny H.W. & Aghimien, Emmanuel I. & Tsang, Ernest K.W., 2022. "Application of artificial neural networks in horizontal luminous efficacy modeling," Renewable Energy, Elsevier, vol. 197(C), pages 864-878.

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