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A Method for Evaluating Options for Motif Detection in Electricity Meter Data

Dent, Ian; Craig, Tony; Aickelin, Uwe; Rodden, Tom


Ian Dent

Tony Craig

Uwe Aickelin

Pro-Vice-Chancellor of Research & Knowledge Exchange


Investigation of household electricity usage patterns, and matching the patterns to behaviours, is an important area of research given the centrality of such patterns in addressing the needs of the electricity industry. Additional knowledge of household behaviours will allow more effective targeting of demand side management (DSM) techniques.
This paper addresses the question as to whether a reasonable number of meaningful motifs, that each represent a regular activity within a domestic household, can be identified solely using the household level electricity meter data.
Using UK data collected from several hundred households in Spring 2011 monitored at a frequency of five minutes, a process for finding repeating short patterns (motifs) is defined. Different ways of representing the motifs exist and a qualitative approach is presented that allows for choosing between the options based on the number of regular behaviours detected (neither too few nor too many).


Dent, I., Craig, T., Aickelin, U., & Rodden, T. (2018). A Method for Evaluating Options for Motif Detection in Electricity Meter Data. International Journal of Data Science, 16(1), 1-28.

Journal Article Type Article
Acceptance Date Dec 5, 2017
Online Publication Date Feb 24, 2021
Publication Date 2018-01
Deposit Date Dec 11, 2017
Publicly Available Date Jan 31, 2018
Journal Journal of Data Science
Print ISSN 2053-0811
Electronic ISSN 1683-8602
Publisher Inderscience
Peer Reviewed Peer Reviewed
Volume 16
Issue 1
Pages 1-28
Keywords Motif detection, Clustering, Electricity Usage
Public URL
Publisher URL


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