The application of a data mining framework to energy usage profiling in domestic residences using UK data
Changes in the UK electricity market mean that domestic users will be required to modify their usage behaviour in order that supplies can be maintained. Clustering allows usage proles collected at the household level to be clustered into groups and assigned a stereotypical prole which can be used t...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2011
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| Online Access: | https://eprints.nottingham.ac.uk/2031/ |
| _version_ | 1848790708892205056 |
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| author | Dent, Ian Aickelin, Uwe Rodden, Tom |
| author_facet | Dent, Ian Aickelin, Uwe Rodden, Tom |
| author_sort | Dent, Ian |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Changes in the UK electricity market mean that domestic
users will be required to modify their usage behaviour in order that supplies can be maintained. Clustering allows usage proles collected at the household level to be clustered into groups and assigned a stereotypical prole which can be used to target marketing campaigns. Fuzzy C Means clustering extends this by allowing each household to be a member of many groups and hence provides the opportunity to make personalised offers to the household dependent on their degree of membership of each group. In addition, feedback can be provided on how user's changing behaviour is moving them towards more "green" or cost effective stereotypical usage. |
| first_indexed | 2025-11-14T18:16:55Z |
| format | Conference or Workshop Item |
| id | nottingham-2031 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:16:55Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-20312020-05-04T20:23:49Z https://eprints.nottingham.ac.uk/2031/ The application of a data mining framework to energy usage profiling in domestic residences using UK data Dent, Ian Aickelin, Uwe Rodden, Tom Changes in the UK electricity market mean that domestic users will be required to modify their usage behaviour in order that supplies can be maintained. Clustering allows usage proles collected at the household level to be clustered into groups and assigned a stereotypical prole which can be used to target marketing campaigns. Fuzzy C Means clustering extends this by allowing each household to be a member of many groups and hence provides the opportunity to make personalised offers to the household dependent on their degree of membership of each group. In addition, feedback can be provided on how user's changing behaviour is moving them towards more "green" or cost effective stereotypical usage. 2011 Conference or Workshop Item PeerReviewed Dent, Ian, Aickelin, Uwe and Rodden, Tom (2011) The application of a data mining framework to energy usage profiling in domestic residences using UK data. In: Buildings Don't Use Energy, People Do: Research Students' Conference, 28 June 2011, Bath, England. (Unpublished) |
| spellingShingle | Dent, Ian Aickelin, Uwe Rodden, Tom The application of a data mining framework to energy usage profiling in domestic residences using UK data |
| title | The application of a data mining framework to energy usage profiling in domestic residences using UK data |
| title_full | The application of a data mining framework to energy usage profiling in domestic residences using UK data |
| title_fullStr | The application of a data mining framework to energy usage profiling in domestic residences using UK data |
| title_full_unstemmed | The application of a data mining framework to energy usage profiling in domestic residences using UK data |
| title_short | The application of a data mining framework to energy usage profiling in domestic residences using UK data |
| title_sort | application of a data mining framework to energy usage profiling in domestic residences using uk data |
| url | https://eprints.nottingham.ac.uk/2031/ |