Title Stochastic Daylighting Model for Predictive Control in Large Open-space Building
Authors 조형곤(Jo, Hyeong-Gon) ; 김영섭(Kim, Young-Sub) ; 박철수(Park, Cheol-Soo)
DOI https://doi.org/10.5659/JAIK.2021.37.12.255
Page pp.255-264
ISSN 2733-6247
Keywords Model Uncertainty; daylight prediction model; Electric Lighting Control; Gaussian Process
Abstract 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.