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The application of a data mining framework to energy usage profiling in domestic residences using UK data

Dent, Ian; Aickelin, Uwe; Rodden, Tom

Authors

Ian Dent

Uwe Aickelin uwe.aickelin@nottingham.ac.uk

Tom Rodden



Abstract

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.

Peer Reviewed Peer Reviewed
APA6 Citation Dent, I., Aickelin, U., & Rodden, T. The application of a data mining framework to energy usage profiling in domestic residences using UK data
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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The_Application_of_a_Data_Mining_Framework_to_Energy_Usage_etc.Student_Conf.Bath.2011.pdf (217 Kb)
PDF

Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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