Variability of behaviour in electricity load profile clustering: who does things at the same time each day?
UK electricity market changes provide opportunities to alter households' electricity usage patterns for the benet of the overall electricity network. Work on clustering similar households has concentrated on daily load proles and the variability in regular household behaviours has not been con...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Book Section |
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Springer International Publishing
2014
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/3347/ |
| _version_ | 1848791006172938240 |
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| author | Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom |
| author2 | Perner, Petra |
| author_facet | Perner, Petra Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom |
| author_sort | Dent, Ian |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | UK electricity market changes provide opportunities to alter
households' electricity usage patterns for the benet of the overall electricity network. Work on clustering similar households has concentrated on daily load proles and the variability in regular household behaviours has not been considered. Those households with most variability in reg-
ular activities may be the most receptive to incentives to change timing. Whether using the variability of regular behaviour allows the creation of more consistent groupings of households is investigated and compared with daily load prole clustering. 204 UK households are analysed to nd
repeating patterns (motifs). Variability in the time of the motif is used as the basis for clustering households. Dierent clustering algorithms are assessed by the consistency of the results.
Findings show that variability of behaviour, using motifs, provides more consistent groupings of households across dierent clustering algorithms and allows for more ecient targeting of behaviour change interventions. |
| first_indexed | 2025-11-14T18:21:38Z |
| format | Book Section |
| id | nottingham-3347 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:21:38Z |
| publishDate | 2014 |
| publisher | Springer International Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-33472020-05-04T20:16:24Z https://eprints.nottingham.ac.uk/3347/ Variability of behaviour in electricity load profile clustering: who does things at the same time each day? Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom UK electricity market changes provide opportunities to alter households' electricity usage patterns for the benet of the overall electricity network. Work on clustering similar households has concentrated on daily load proles and the variability in regular household behaviours has not been considered. Those households with most variability in reg- ular activities may be the most receptive to incentives to change timing. Whether using the variability of regular behaviour allows the creation of more consistent groupings of households is investigated and compared with daily load prole clustering. 204 UK households are analysed to nd repeating patterns (motifs). Variability in the time of the motif is used as the basis for clustering households. Dierent clustering algorithms are assessed by the consistency of the results. Findings show that variability of behaviour, using motifs, provides more consistent groupings of households across dierent clustering algorithms and allows for more ecient targeting of behaviour change interventions. Springer International Publishing Perner, Petra 2014 Book Section PeerReviewed Dent, Ian, Craig, Tony, Aickelin, Uwe and Rodden, Tom (2014) Variability of behaviour in electricity load profile clustering: who does things at the same time each day? In: Advances in data mining: applications and theoretical aspects: 14th Industrial Conference, ICDM 2014, St. Petersburg, Russia, July 16-20, 2014: proceedings. Lecture notes in computer science (8557). Springer International Publishing, Cham, pp. 70-84. ISBN 9783319089768 (electronic bk.); 9783319089751 (print) Data Mining Digital Economy http://link.springer.com/chapter/10.1007/978-3-319-08976-8_6 doi:10.1007/978-3-319-08976-8_6 doi:10.1007/978-3-319-08976-8_6 |
| spellingShingle | Data Mining Digital Economy Dent, Ian Craig, Tony Aickelin, Uwe Rodden, Tom Variability of behaviour in electricity load profile clustering: who does things at the same time each day? |
| title | Variability of behaviour in electricity load profile clustering: who does things at the same time each day? |
| title_full | Variability of behaviour in electricity load profile clustering: who does things at the same time each day? |
| title_fullStr | Variability of behaviour in electricity load profile clustering: who does things at the same time each day? |
| title_full_unstemmed | Variability of behaviour in electricity load profile clustering: who does things at the same time each day? |
| title_short | Variability of behaviour in electricity load profile clustering: who does things at the same time each day? |
| title_sort | variability of behaviour in electricity load profile clustering: who does things at the same time each day? |
| topic | Data Mining Digital Economy |
| url | https://eprints.nottingham.ac.uk/3347/ https://eprints.nottingham.ac.uk/3347/ https://eprints.nottingham.ac.uk/3347/ |