A method for evaluating options for motif detection in electricity meter data
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...
| Main Authors: | , , , |
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| Format: | Article |
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Tingmao Publishing Co.
2018
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| Online Access: | https://eprints.nottingham.ac.uk/48612/ |
| _version_ | 1848797806879309824 |
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| author | Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom |
| author_facet | Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom |
| author_sort | Dent, Ian |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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). |
| first_indexed | 2025-11-14T20:09:44Z |
| format | Article |
| id | nottingham-48612 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:09:44Z |
| publishDate | 2018 |
| publisher | Tingmao Publishing Co. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-486122020-05-04T19:28:56Z https://eprints.nottingham.ac.uk/48612/ A method for evaluating options for motif detection in electricity meter data Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom 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). Tingmao Publishing Co. 2018-01-31 Article PeerReviewed Dent, Ian, Craig, Tony, Aickelin, Uwe and Rodden, Tom (2018) A method for evaluating options for motif detection in electricity meter data. Journal of Data Science, 16 (1). ISSN 1683-8602 Motif detection Clustering Electricity Usage http://www.jds-online.com/volume-16-number-1-january-2018 |
| spellingShingle | Motif detection Clustering Electricity Usage Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom A method for evaluating options for motif detection in electricity meter data |
| title | A method for evaluating options for motif detection in
electricity meter data |
| title_full | A method for evaluating options for motif detection in
electricity meter data |
| title_fullStr | A method for evaluating options for motif detection in
electricity meter data |
| title_full_unstemmed | A method for evaluating options for motif detection in
electricity meter data |
| title_short | A method for evaluating options for motif detection in
electricity meter data |
| title_sort | method for evaluating options for motif detection in
electricity meter data |
| topic | Motif detection Clustering Electricity Usage |
| url | https://eprints.nottingham.ac.uk/48612/ https://eprints.nottingham.ac.uk/48612/ |