AUTHOR=Tsang Ernest Kin Wai , Li Danny Hin Wa , Li Shuyang TITLE=Predicting Daylight Illuminance for 15 CIE Standard Skies Using a Simple Software Tool JOURNAL=Frontiers in Sustainable Cities VOLUME=4 YEAR=2022 URL=https://www.frontiersin.org/journals/sustainable-cities/articles/10.3389/frsc.2022.792997 DOI=10.3389/frsc.2022.792997 ISSN=2624-9634 ABSTRACT=

Estimation of internal daylight availability is the key step in evaluating various daylighting schemes. Interior daylight is often expressed as daylight factor under the traditional International Commission on Illumination (CIE) overcast sky. Nonetheless, such approach may be inflexible to estimate the kinetic situations as the solar locations vary under cloudless skies. Recently, the CIE adopted 15 standard skies covering the usual skies found in the world. The interior daylight illuminance is influenced by the sky conditions in terms of luminance levels and distributions with respect to the window-facing orientation at any given period. The daylight coefficient concept considering the variations of the sky luminance patterns can be employed to accurately compute the indoor daylight level. A full-scale computer simulation can be costly in modeling the building geometry with a long simulation time. Moreover, additional times and advanced skills are required for preparation and post-processing. Simple design programs would be convenient and helpful in preliminary design phase when various designs and schemes are being studied and analyzed. This paper adopts a simple computer program for computing the interior daylight under the 15 CIE standard skies. The capability of the suggested software was assessed against the simulated results using a computer program, namely, RADIANCE, and the field measurement readings. The running time based on the simple program was far less than that using RADIANCE. The findings showed that the internal daylight simulated by the proposed simple software were in good agreement with the simulated results by RADIANCE and measured readings. The peak daylight factor discrepancy was <2%, and the RMSE was 14.5% of the corresponding measured average values.