Development and demonstration of an energy feedback research platform in a field study with real-time social comparisons

Providing residential tenants with feedback on their energy use can be an effective intervention, promoting savings ranging from 4-12%. However, advancements in feedback design have been hindered by methodological limitations, the lack of specification of visual feedback designs, and a poor understanding of the behaviour changes that are induced by feedback. This thesis presents the design and demonstration of an Internet-of-Things-based feedback research platform, which was intended to help address these issues, and which will be made freely available for re-use and reconfiguration. Configured for a rental apartment building in Toronto, Canada, the platform was a central component of a conservation program and field study examining the efficacy of real-time social comparisons. Results showed a statistically significant effect of the conservation program with a relative year-over-year, weather-normalized savings of approximately 11%. An encouraging, but non-significant, finding of a 3.5% relative improvement with real-time social comparisons warrants future large scale studies.