Identifying the time profile of everyday activities in the home using smart meter data

Activities are a descriptive term for the common ways households spend their time. Examples include cooking, doing laundry, or socialising. Smart meter data can be used to generate time profiles of activities that are meaningful to households’ own lived experience. Activities are therefore a lens through which energy feedback to households can be made salient and understandable. This paper demonstrates a multi-step methodology for inferring hourly time profiles of ten household activities using smart meter data, supplemented by individual appliance plug monitors and environmental sensors. First, household interviews, video ethnography, and technology surveys are used to identify appliances and devices in the home, and their roles in specific activities. Second, ‘ontologies’ are developed to map out the relationships between activities and technologies in the home. One or more technologies may indicate the occurrence of certain activities. Third, data from smart meters, plug monitors and sensor data are collected. Smart meter data measuring aggregate electricity use are disaggregated and processed together with the plug monitor and sensor data to identify when and for how long different activities are occurring. Sensor data are particularly useful for activities that are not always associated with an energy-using device. Fourth, the ontologies are applied to the disaggregated data to make inferences on hourly time profiles of ten everyday activities. These include washing, doing laundry, watching TV (reliably inferred), and cleaning, socialising, working (inferred with uncertainties). Fifth, activity time diaries and structured interviews are used to validate both the ontologies and the inferred activity time profiles. Two case study homes are used to illustrate the methodology using data collected as part of a UK trial of smart home technologies. The methodology is demonstrated to produce reliable time profiles of a range of domestic activities that are meaningful to households. The methodology also emphasises the value of integrating coded interview and video ethnography data into both the development of the activity inference process

Supporting retrofit decisions using smart meter data: a multi-disciplinary approach

The UK Government’s flagship energy efficiency program, the Green Deal, provides retrofit advice for household occupants based on a technical house survey and an engineering modelling tool. Smart meter data provides an opportunity to give bespoke advice to occupants based on the actual performance of their home and their own heating practices as well as visualisations of hourly and daily energy use. This work presents initial results from one component of a complex multidisciplinary research project which aims to use smart meter and smart home data to design and develop retrofit decision support concepts. Home visits involving creative design based research activities were carried out in five homes. Household occupants were presented with two types of energy use report; 1) a Green Deal advice report which includes suggested retrofit measures and annual energy consumption figures based on a steady state modelling approach and; 2) a personalised energy use report, based on smart meter data collected in their homes over a 12 month period. The home visits were carried out with the occupants to discuss a range of possible retrofit measures and gather feedback regarding the communication method for advice about energy efficiency improvements. Initial findings from the home visits indicate that the provision of energy feedback using smart meter data did not directly influence the occupants to make energy efficient retrofits any more than the Green Deal advice reports. However, the visualisation of actual hourly and daily energy use enabled householders to make links with their lived experience and stimulated discussions about their energy use which may impact on their preconceived ideas about energy use and energy efficiency measures