DOI: 10.25549/usctheses-c40-366191
title: A systematic approach to understand and model the impact of lighting behavior on building energy consumption through immersive virtual environments

description: In recent years, studies have identified that occupant behavior and preferences significantly influence the total energy consumption in buildings. However, the lack of available occupant-related information and understanding how different factors may influence occupant behavior and interactions with building systems, has resulted in inefficient system operations and higher energy consumption during the operation phase of buildings. In this research, a systematic approach is defined to (I) collect a large amount of occupant-related information in different design and operational settings, (II) identify the relationships between occupant behavior and building energy consumption, and (III) reason how such relationships can be used to improve the design and operation of buildings. To gather occupant-related information, an innovative approach was introduced to use immersive virtual environments (IVEs) as experimental tools to collect behavioral information by allowing participants interact with different design features and building systems (i.e., artificial lighting systems, blinds, control options). To ensure the collected data in IVEs is a proper representation of physical settings, a benchmarking study was conducted to identify if there is a significant difference between participants’ performance, sense of presence, perception, and immersion between the two mediums (IVE vs. physical environment). After identifying that IVEs can be used to collect realistic occupant-related information, three IVE-based experimental studies were conducted, in which (1) the influence of semi-automated lighting and shading control options on participants’ choice of lighting (daylighting vs. electric lighting) was analyzed; (2) participant choice of lighting was collected to better understand how end-user preferences, personality traits, and environmentally friendliness may influence choice of lighting; and (3) psychological concepts, such as default settings, were implemented in order to understand participants’ propensity to keep or adjust the initial lighting and shading settings when provided with different defaults options. The identified user-profiles were then used to define a set of behavioral models for predicting the relationship between lighting preferences, performance, personality traits, and participants’ interactions with the lighting and shading systems in different default settings. These models were integrated into a Building Performance Simulations (BPS) tool to better understand the impact of occupant behavior on the building energy consumption. The findings of this research indicate that by having access to user behavior and preferential information, BPS tools can better predict the total energy consumption in buildings and design teams can make user-centered design decisions; psychological factors such as personality traits and defaults were determined as influential factors that can be used to reduce the building energy consumption; additionally, IVEs were identified as effective experimental tools for collecting realistic lighting-related information in office environments. Lastly, the defined systematic approach allows for effectively integrating user-centered thinking into design and operation of buildings to better meet the occupants’ needs and preferences while reducing the building energy consumption.