Exploratory analysis of family-related activities during peak electricity periods

Panel: 1. The dynamics of limiting (energy) consumption

This is a peer-reviewed paper.

Authors:
Máté Lőrincz, University of Reading, United Kingdom
Timur Yunusov, School of Built Environment, University of Reading, United Kingdom
Jacopo Torriti, School of Built Environment, University of Reading, United Kingdom

Abstract

Price-based interventions (such as Time of Use tariffs) are designed to shift the timing of certain everyday activities to mitigate peak electricity demand.On the one hand, it is argued that timing activities outside the peak hours would decrease the demand, easing the stress on the grid.On the other hand, recent literature suggests that householders are more likely to ignore timing of activities - due to convenience or due to activities considered 'non-negotiable' during peak hours. One way to address this conundrum is to investigate how family-related activities during the peak times hang together and what is important about performing them together at a specific time of the day.

The starting point of this research is that working hours and school times shape the dynamics of peak hours, leaving less time for families to do more during these time periods and also making it difficult to shift activities to other times of the day. Drawing on the insight of our preliminary analysis, using UK Time Use Survey 2014-2015 diaries, we diagram family-related activities (such as homework, food preparation, cleaning, washing, bathing or playing) which constitute the outside peak electricity period, as well as those performed during the peak electricity period (4pm–8pm). We aim to explore the timing and duration of activities and how they vary at different temporal and spatial scales. Markov chain technique will be used to determine the probability of a certain electricity load to take place at a specific time of a day.

In conclusion, we argue that any effective shifting of family-related activities will need to look beyond the meter (such as de-synchronized effects of school holidays), potentially collecting information regarding both energy and non-energy data in order to understand the connection, coordination and organization between activities which constitute electricity demand.