OCCUPANT BEHAVIOR IN BUILDING ENERGY MANAGEMENT: BEHAVIORAL CHARACTERIZATION, INTERVENTION AND FORECASTING

Abstract

With the advent of the climate change and global warming, there is a need to adopt a diversified approach to address climate change; this is especially the case of promoting building energy conservation. This dissertation is one of the first studies that focuses on the occupant behavior in the building energy conservation, in particular three dimensions. First, this study aims to propose a behavior-based model that investigates impact of renters’ rebound effect on building retrofit saving amount and to design the shared saving scheme among major stakeholders during their decision-making process. With demonstration of a real retrofitting project in a university campus, the rebound effect was identified to significantly extend the payback period of retrofit contracts and such the prolonged duration is partially determined by renters’ risk attitudes towards monetary incentives. Second, the study compares two message delivering means, paper-based (e.g. stickers) versus instant messaging tool (e.g. WeChat), as a platform for sharing energy-saving information and promoting occupant energy conservation in China. It was found that WeChat is the most effective intervention in reducing energy consumption, but the effects are short-lived. Using stickers, comparatively, produces more sustained results with long-term engagement of households. The changes in certain occupant energy behaviors are also correlated with individuals’ perception of responsibility and quality of life to explain the heterogeneity of individual behaviors. Third, the study examines the interaction effect between occupant personality, energy behavior and intervention strategies with algorithms that can identify the optimal intervention strategy tailored for each household. This is followed by an improved Support Vector Regression (SVR) model that is capable of predicting household electricity consumption under optimal intervention strategies according to occupant behavior and personality traits. The proposed intervention lead to an average reduction of 12.1% in monthly household energy consumption compared with conventional behavioral interventions. The methods and algorithms developed from this study are pioneer works providing implications to measure the influence of occupant behaviors on energy saving amounts, to enrich and diversify behavioral intervention strategies, and to design incentives, programs and policies that effectively regulate occupant behaviors, collectively contributing to the demand-side energy management in buildings.