Household Electricity Consumption Routines and Tailored Feedback

Evidence suggests that rational alternatives do not necessarily drive the choices made by real individuals in the privacy of their homes, Therefore, an understanding of the characteristics of the utility’s customer base, is useful to help design utility programs that target the customer’s ordinary daily practices. This paper summarizes the main results of a method to highlight familial habits by datamining electricity consumption datasets. Target families were participants in a small-scale experiment that resembles a utility led advanced meter infrastructure implementation. The process highlights load shapes, which occur more frequently for days with similar characteristics. Approximately 80% of the household electrical use can be explained within those load trends. These include: load shape for unoccupied baseline, hot working days, temperate days, cold working and cold weekend days. We conclude with a discussion of possible applications of the electricity consumption trends for feedback and segmentation.