지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.12
- 수록면
- 255 - 264 (10page)
이용수
초록· 키워드
오류제보하기
Development of stochastic daylighting prediction model for a large open-space building was presented in this paper. The daylit prediction model uses solar altitude and azimuth, an illuminance value at a reference point and a cloud cover and predict daylit illuminances at sixteen workplane. The model can be regarded as ‘virtual sensor’ without installing actual photosensor. For capturing stochastic characteristics of daylit luminous indoor environment, Gaussian process was used. The daylit prediction model was then integrated to electric lighting control of the building. The optimal lighting control variables that can minimize electric lighting power consumption while satisfying required illuminance level expressed as a safety margin were found. Based on the eight days’ validation, it is found that the proposed approach could save energy by 12.3%. It is expected that this stochastic control approach could be applied to other lighting control or indoor environmental control system.
목차
Abstract
1. 서론
2. 대상건물
3. 자연채광 조도 예측 모델
4. 전기조명 제어
5. 결론
REFERENCES
참고문헌 (31)
참고문헌 신청
Ayoub, M. (2019). 100 Years of daylihgting: A chronological review of daylight prediction and calculation methods, Solar Energy, 194, 360-390.
Afshari, S. & Mishra, S. (2016). A plug-and-play realization of decentralized feedback control for smart lighting systems
Borile, S., Pandharipande, A., Caicedo, D., Schenato, L. & Cenedese, A. (2017). A data-driven daylight estimation approach to lighting control, IEEE Access, 5, 21461-21471.
Caicedo, D., Pandharipande, A., & Willems, F. M. J. (2014). Daylight-adapted lighting control using light sensor calibration prior-information, Energy and Buildings, 73, 105-114.
Delvaeye, R., Ryckaert, W., Stroobant, L., Hanslaer, P., Klein, R., & Breesch, H. (2016). Analysis of senergy savings of three daylight control systems in a school building by means of monitoring, Energy and Buildings, 127, 969-979.
Afshari, S. & Mishra, S. (2016). A plug-and-play realization of decentralized feedback control for smart lighting systems
Borile, S., Pandharipande, A., Caicedo, D., Schenato, L. & Cenedese, A. (2017). A data-driven daylight estimation approach to lighting control, IEEE Access, 5, 21461-21471.
Caicedo, D., Pandharipande, A., & Willems, F. M. J. (2014). Daylight-adapted lighting control using light sensor calibration prior-information, Energy and Buildings, 73, 105-114.
Delvaeye, R., Ryckaert, W., Stroobant, L., Hanslaer, P., Klein, R., & Breesch, H. (2016). Analysis of senergy savings of three daylight control systems in a school building by means of monitoring, Energy and Buildings, 127, 969-979.
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