A Method for Evaluating Options for Motif Detection in Electricity Meter Data
AuthorDent, I; Craig, T; Aickelin, U; Rodden, T
Source TitleJournal of Data Science
PublisherColumbia University, New York
University of Melbourne Author/sAickelin, Uwe
AffiliationEngineering Collected Works
Document TypeJournal Article
CitationsDent, I., Craig, T., Aickelin, U. & Rodden, T. (2018). A Method for Evaluating Options for Motif Detection in Electricity Meter Data. Journal of Data Science, 16 (1), pp.1-28. https://doi.org/10.1080/01605682.2017.1410010.
Access StatusOpen Access
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).
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