Accuracy analysis of computational algorithms for prediction of daylight illuminance in space with shading devices

Younju Yoon, Jin Woo Moon, Hussain H. Alzoubi, Sooyoung Kim

Research output: Contribution to journalArticle

Abstract

This study examines the accuracy of annual daylight simulation method (ADSM) in predicting illuminance for spaces with shading device conditions. ADSM algorithms were developed separately for the sun and sky to predict their effect on indoor daylight illuminance. Sun-matching and daylight coefficient methods were developed for the sun, while sky-matching and daylight coefficient methods with one and four sky patches were developed for the sky. The daylight illuminance computed from ADSM under various daylight conditions was compared with those calculated from Radiance and field measurements. Results imply strong linear correlations existed between the predicted daylight illuminance levels by the ADSM and Radiance under diverse sky conditions based on weather data. The predicted illuminance from ADSM was lower than field measurements for all sky conditions. ADSM computations mostly agree with field measurements. For clear and partly cloudy sky conditions, the daylight coefficient approach for sky of ADSM generated a stronger correlation to measured data, but the sky-matching algorithm showed a stronger correlation to field data. The daylight coefficient approach for sky, combined with ADSM computation algorithms for sun, effectively reduced the difference between the predicted and measured illuminance under clear or partly cloudy sky conditions. Under overcast conditions, there was no significant reduction in difference between simulated and measured illuminance.

Original languageEnglish
Pages (from-to)700-717
Number of pages18
JournalSolar Energy
Volume153
DOIs
Publication statusPublished - 2017 Jan 1

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All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Materials Science(all)

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