Conference Paper
Proceedings of Building Simulation 2021: 17th Conference of IBPSA
A simplified open-loop control strategy for integrated shading and lighting systems using machine learning
A simplified open-loop control strategy for integrated shading and lighting systems using machine learning
Jiarong Xie, Azadeh Omidfar SawyerCarnegie Mellon University, United States of AmericaDOI: https://doi.org/10.26868/25222708.2021.30629Abstract: Conventional integrated shading and lighting systems are usually sensor-dependent, which could entail excessive cost and labor associated with sensor installation, calibration, and maintenance. Advanced systems use daylight modeling to eliminate the use of physical sensors. However, real-time daylight simulation can be computation-heavy, leading to a slow response of the system. This paper proposed a data-driven method for integrated shading and lighting control, employing machine learning models developed from pre-simulated data to predict real-time daylighting and control the blind and lighting accordingly. Verification using climatebased daylight simulation with a case study showed that the method prevented 94.7% of annual glare and reduced lighting use by 64%. The study will contribute to the development of effective daylight-linked control systems for industrial applications. Keywords: Glare control, automated shading system, data-driven method, daylight simulationPages: 3172 - 3179 Paper:![]()
