Abstract

Identification and quantitative understanding of factors that influence occupant energy behavior and thermal state during the design phase are critical in supporting effective energy-efficient design. To achieve this, immersive virtual environments (IVEs) have recently shown potential as a tool to simulate occupant energy behaviors and collect context-dependent behavior data for buildings under design. On the other hand, prior models of occupant energy behaviors and thermal states used correlation-based approaches, which failed to capture the underlying causal interactions between the influencing factors and hence were unable to uncover the true causing factors. Therefore, in this study, the authors investigate the applicability of causal inference for identifying the causing factors of occupant/participant energy behavioral intentions and their thermal states in IVE condition and compare those results with the baseline in-situ condition. The energy behavioral intentions here are a proximal antecedent of actual energy behaviors. A set of experiments involving 72 human subjects were performed through the use of a head-mounted device (HMD) in a climate chamber. The subjects were exposed to three different step temperatures (cool, neutral, warm) under an IVE and a baseline in-situ condition. Participants' individual factors, behavioral factors, skin temperatures, virtual experience factors, thermal states (sensation, acceptability, comfort), and energy behavioral intentions were collected during the experiments. Structural causal models were learnt from data using the elicitation method in conjunction with the PC-Stable algorithm. The findings show that the causal inference framework is a potentially effective method for identifying causing factors of thermal states and energy behavioral intentions as well as quantifying their causal effects. In addition, the study shows that in IVE experiments, the participants' virtual experience factors such as their immersion, presence, and cybersickness were not the causing factors of thermal states and energy behavioral intentions. Furthermore, the study suggests that participants' behavioral factors such as their attitudes toward energy conservation and perceived behavioral control to conserve energy were the causing factors of their energy behavioral intentions. Also, the indoor temperature was a causing factor of general thermal sensation and overall skin temperature. The paper also discusses other findings, including discrepancies, limitations of the study, and recommendations for future studies.

Highlights

  • Occupants interact with the components of building systems in a variety of ways to achieve their desired comfort level, thereby influencing the indoor environment and overall energy use of the buildings

  • In a structural causal model (SCM), we can look at the direction of network arcs that flow from one factor to another to interpret the causal relationship between them

  • Two alternative SCMs were developed to estimate the causal effect of exclusive breastfeeding (EBF) on early childhood caries (ECC) for Ugandan kids aged 5 (Birungi et al, 2017)

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Summary

Introduction

Occupants interact with the components of building systems in a variety of ways to achieve their desired comfort level, thereby influencing the indoor environment and overall energy use of the buildings. State-of-the-art studies and extensive literature reviews confirm that accurate occupant energy behavior analysis during design is critical to closing the gap between expected and real building energy efficiency (Maier et al, 2009; Fabi et al, 2013b; Martinaitis et al, 2015; Schakib-Ekbatan et al, 2015; Calì et al, 2016; Yang et al, 2016). This energy behavior is influenced by many factors. The above studies followed conventional modeling approaches, and the results are interpreted as correlations rather than causation

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