Journal of the Architectural Institute of Korea (대한건축학회논문집)

Architectural Institute of Korea (대한건축학회)
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Evaluation of Visual Comfort and Lighting Energy in a Residential Building Equipped with Suspended Particle Device Smart Window Based on In-situ Measurement

계측을 통한 스마트윈도우 적용 주거건물의 빛환경 및 조명에너지 분석

  • Lee, Soo-Jin (Dept. of Architectural & Urban Systems Engineering, Ewha Womans University) ;
  • Song, Seung-Yeong (Dept. of Architectural & Urban Systems Engineering, Ewha Womans University)
  • 이수진 (이화여자대학교 건축도시시스템공학과) ;
  • 송승영 (이화여자대학교 건축도시시스템공학과)
  • Received : 2023.01.04
  • Accepted : 2023.04.06
  • Published : 2023.05.30
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Abstract

The purpose of this study is to evaluate the performance of visual comfort and lighting energy according to the application of smart windows based on in-situ measurement. To this end, suspended particle device smart windows were applied to an apartment building, which is representative residential building in Korea, related sensors and equipment were installed, and data was collected over '22.07~09. In addition, the evaluation items for visual comfort were set with glare and indoor daylight illuminance, and each evaluation indicator adopted DGI (Daylight Glare Index) and UDI (Useful Daylight Illuminance). Energy performance evaluation was analyzed through lighting energy consumption. In the case of cloudy day, glare did not occur in the control group, so it was found that glare control by smart window discoloration was unnecessary. In the case of partly cloudy day and the clear day, regardless of the smart window control method, the DGI value was always below 22 when applying the smart window, which was found to be effective for glare control. In terms of promoting UDI and reducing lighting energy consumption, it was found to be effective in controlling smart window discoloration rather than always discoloring smart windows under all sky condition. And it was found that the difference in effect was not large when the discoloration reference value was 200 lx or 400 lx.

Keywords

Acknowledgement

이 연구는 2023년도 국토교통부 AI기반 스마트하우징기술개발사업 연구비 지원에 의한 결과의 일부임. 과제번호: RS-2020-KA157018

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