Abstract

Automated shading and lighting control systems can be used to control solar radiation and daylight entering the space and reduce the lighting requirement, providing both energy savings and better visual comfort for occupants. Past studies that have explored automated lighting and shading control strategies typically report energy savings and visual comfort improvements over their respective baselines. However, across different studies, the assumptions for baseline models differ, as many daylighting studies use an experimental setup to measure various daylighting-based metrics to evaluate the performance of their control strategies in a real building. For instance, these actual buildings usually have different room sizes (depth and width), different window locations (height, width, and WWR (with/without split windows), window orientation (simultaneous windows in two directions), glazing properties and climate zones of the building location. As these input variables affect the result of daylighting studies, comparing percent improvement in energy savings due to the implemented control strategies across different papers can be challenging. This research uses a common baseline to evaluate the differences between a broad diversity of existing lighting and shading control strategies. The author also proposes an Integrated Control Strategy (IGS), which accounts for variables such as occupancy, HVAC state, solar radiation entering the space, and time of day for control. This study uses a multi-step modeling process, including daylighting and energy simulations using RADIANCE and EnergyPlus, respectively, in a Ladybug and Honeybee plugin environment. The results are used to quantify the differences in the existing control strategies to a common baseline model. The results suggest that complex rule based shading and lighting strategies such as an IGS performs only slightly better (6–12 % decrease in view to the outside, no glare, 82–88% lighting energy savings and 7.5–14.5% total energy savings compared shades fully open) when compared to existing glare metric based control strategy (4.5–9.5 % decrease in view to the outside, no glare, 63–72% lighting energy savings and 7–13% total laod savings compared shades fully open. Thus, if the addition of sensors is needed to support complex shading and lighting controls strategies, these sensors may benefit from being used for multiple purposes in order to justify their use.

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