Adaptive façade controls: A methodology based on occupant visual comfort preferences and cluster analysis

2018-07-26A static daylighting façade system creates varying and uncontrolled levels of daylighting and visual conditions in a space. These visual comfort conditions are evaluated based on standard requirements or averaged visual comfort preference ranges that might not reflect true individual preferences. Such a control strategy, therefore, fails to address stochastic phenomena, such as changing, and often competing, individual visual comfort requirements and bias, and factors such as occupant position and viewing direction in a space. An adaptive daylighting façade system can consist of multiple independently-controllable components that are driven by a control logic which determines its control states. Using an objective function and through quantification of the required features, a control logic can assist in finding one or more possible daylighting system configurations that most closely produce certain predetermined criteria, such as glare or illuminance. For a multiple-occupancy condition, a set of individual and cumulative dissatisfaction indices were proposed that represented and helped quantify how effective an adaptive façade configuration was in producing the occupant-preferred sets of visual comfort performance. In a case study, adaptive facade configurations at 15-minute intervals were ranked based on their performance, finding control states that affected the results the most, developing and improving daylighting control strategies, and providing a more personal and generally satisfactory and controlled daylit environment. The dynamic real-time control logic framework accounted for three visual comfort factors: average task surface illuminance, glare, and task surface to background luminance contrast ratio. The south-east corner of an existing open-plan office in downtown Los Angeles was modeled with electrochromic vision glazing, kinetic shading, and light shelves. Using the Grasshopper and Honeybee interfaces, daylighting simulations under climate-based sky conditions were performed for three times daily for three days of the year to evaluate the proposed framework. The framework integrated a simplified occupant preference model with a simplified glare calculation method and a Radiance-based illuminance-luminance simulation workflow, using calculation and data analysis modules. Python was used to create a normalized distribution of personal occupant visual comfort ranges based on predefined lists and to generate flat importance factors, for glare, illuminance, and contrast ratio. The variations of each measured occupant comfort value from the preferred range, weighted by their respective importance factors, was calculated to provide a net deviation value for each occupant. A brute force simulation method was used to generate all possible façade configurations, and the respective visual comfort factor deviation values were then recorded, analyzed, and compared against a baseline case. The proposed framework substantially increased the overall as well as individual percentage occupant visual satisfaction in a multiple occupancy condition in comparison with the baseline case. A substantial reduction of cumulative deviation from the baseline case was observed for certain façade configurations, thus validating that the proposed control framework can be used to optimize façade control states that improve the overall occupant satisfaction with the visual environment by making more people more satisfied with their visual task environment. Analyses of the control states of the high performing façade configurations were useful in developing daylighting control strategies and to find adaptive façade elements and states that have the most effect on the visual comfort condition at different times of the year