How do users understand and act upon disaggregated feedback in Smappee?

Abstract: Giving feedback to households about their energy consumption has been seen by many as a necessity in order for households to reduce their energy consumption and lower their carbon footprint. Many studies have been made on how smart meters, that give feedback on the total consumption, are used and their effect on the consumption. However, fewer studies have been done on how disaggregated feedback is understood and acted upon. Smappee is an energy feedback system that monitors the household’s consumption and is able to detect appliances’ consumption with only 3 physical clamps at the incoming current, using non-intrusive load monitoring (NILM). NILM differentiate appliances based on their electrical signature which is generated by turning an appliance on and off. The users get the feedback through a smartphone application. This study attempts to answer the question “How do users understand and act upon disaggregated feedback in Smappee?” by doing a qualitative study based on contextual interviews made on 15 users of Smappee. The results of the interviews are then compared with previous studies within the field of smart meters and a conceptual model is being described of how users understand Smappee. The results show that disaggregated feedback in Smappee is perceived as too difficult to acquire. Users thought it was too hard to find which appliances represented in Smappee correspond to which physical appliances in the household. However, the users used the real-time total consumption in order to make an estimation of how much certain appliances consumed. This indicates that users are interested in disaggregated feedback if it is easily accessible. Users have, in general, a good understanding of how Smappee detects appliances. They understand that Smappee is measuring the incoming current and makes assumptions based on the increases and decreases. They did not use the disaggregated feedback, even though they understood how it worked.