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Open AccessArticle

An Evaluation of the Ceiling Depth’s Impact on Skylight Energy Performance Predictions Through a Building Simulation

Department of Architectural Engineering, University of Ulsan, Ulsan 44610, Korea
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Sustainability 2020, 12(8), 3117; https://doi.org/10.3390/su12083117
Received: 20 March 2020 / Revised: 10 April 2020 / Accepted: 10 April 2020 / Published: 13 April 2020
(This article belongs to the Section Energy Sustainability)
This study evaluated the impact of including a building ceiling depth into a simulation model on skylight efficiency under two climatic conditions (Ulsan and Seoul, South Korea). Using Radiance and EnergyPlus simulation tools integrated in OpenStudio program by National Renewable Energy Laboratory, Golden, Colorado, USA, daylighting and building energy consumption were computed and assessed to evaluate the energy performance and optimization of skylights. Skylight-to-roof ratios from 1% to 25% were analyzed with ceiling depths of 1.5 m to 3 m. The results showed that the range for efficient skylight ratios became smaller with an increase of ceiling depth; in addition, small apertures were more affected by the ceiling depth than were large apertures. Under Ulsan’s climatic conditions, the optimal skylight-to-roof ratios were 8%, 9%, 10%, and 11% for ceiling depths of 1.5 m, 2 m, 2.5 m, and 3 m, respectively. In Seoul, 8% and 9% were the optimum skylight-to-roof ratios for ceiling depths of 1.5 m and 2 m, respectively; no skylight was energy efficient for a ceiling deeper than 2 m. This study indicates that ceiling depth is a critical factor in the evaluation of skylight performance; thus, it should not be excluded from a simulation model, as is often done to simplify simulation modeling. View Full-Text
Keywords: skylight; ceiling depth; energy efficiency; useful daylight illuminance skylight; ceiling depth; energy efficiency; useful daylight illuminance
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MDPI and ACS Style

Irakoze, A.; Lee, Y.-A.; Kim, K.H. An Evaluation of the Ceiling Depth’s Impact on Skylight Energy Performance Predictions Through a Building Simulation. Sustainability 2020, 12, 3117.

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