Comparing Occupant Self-Assessed Behaviour to Actual Metered Consumption

A post-­occupancy evaluation (POE) is a comprehensive building performance review that includes occupant surveys and provides feedback on the overall success of a building design in addressing end-­‐user requirements. In doing so, POE often identifies disparities between expected and actual energy usage patterns. Part of determining the source of these disparities is the evaluation of tenant responses. Since these are heavily dependent on the users’ ability to accurately recall their usage patterns, their potential inaccuracy may misinform building retrofits and future projects. This study seeks to compare occupant self-­‐assessed behaviour to actual metered consumption. A recently retrofit multi-­‐unit residential building (MURB) and Tower Renewal pilot project was selected for the evaluation, and access to the electricity consumption of the pilot was obtained from building management. The project has 146 units, each approximately 20.5m A post-­‐retrofit survey has been carried out, which amongst other factors attempted to collect information on small appliances and electronics and their use. 48 valid samples were obtained. The monthly electricity consumption of each unit has been calculated based on the tenant responses, and these values have been compared to actual consumption values from the electronic meters. The average estimated consumption was found to be 45% more than the average metered consumption, with 46% of the survey-­‐based estimates exceeding their respective metered readings by more than 50%. As many as 86% of tenants whose consumption estimate exceeded 50% of the metered value incurred time overestimation, while 23% incurred statistical bias. It was also found that all tenants who incurred statistical bias also incurred time overestimation. While individual estimates tend to disagree with metered data, large-­‐sample assessments may still be possible. Mode-­‐based assessments help to limit sources of discrepancy by eliminating tenant responses that occur infrequently, thus creating sample cases that resemble the contents of a ‘typical unit’. However, great care must be taken to avoid introducing further bias. To this end, more rigorous statistical analysis is required. It is recommended that future surveys avoid overestimation by arranging time-­‐related questions in a manner that allows quick revision, tightening the ranges for usage questions to minimize assumptions made, and including relevant custom-­‐made questions that either clarify questions for the tenants or minimize ambiguity in the results.