What we do matters – a time-use app to capture energy relevant activities

Conference item

High expectations rest on demand side response to aid the reliability of future electricity systems and to reduce costs. The extent of the potential contribution depends among other things on what that demand is used for. Some uses could be more flexible than others. Some may respond to price signals, others may require different forms of incentive or changes to material or social contexts. Our understanding of the temporal relationship between the activities and the resulting electricity patterns is still in its infancy.

This paper presents a novel research tool to combine electricity data collection with activity information at the household level. We critically review established methods to time-use collection and propose a range of innovations to improve their suitability for energy related research with the aim to establish ‘what people use electricity for’. Innovations include: 1) A six-way decision tree allows to discriminate 714 in-home activities with fewer than five screen interaction. 2) The recording of instances in time (‘constructive time perspective’) greatly reduces the user-interface complexity. 3) Virtual rewards have been shown to improve participation and even introduce a degree of recording competitiveness within households.

The functionality of this open source mobile app is presented alongside feedback and data from its deployments in UK households. We discuss advantages and drawbacks of this approach in relation to conventional paper-based methods and point towards future research opportunities this approach could enable.

Authors: Grunewald, P; Diakonova, M; Zilli, D; Bernard, J; Matousek, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: European Council for an Energy Efficient Economy
• Host title: eceee 2017 Summer Study
• Journal: eceee 2017 Summer Study
• Publication date: 2017-06-01
• Acceptance date: 2017-05-10
• Keywords: social practices; activity patterns; electricity use; demand patterns; demand analysis