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Creating Personalised Energy Plans: From Groups to Individuals using Fuzzy C Means Clustering [Extended Abstract]

By Ian Dent, Christian Wagner, Uwe Aickelin and Tom Rodden

Abstract

Changes in the UK electricity market mean that domestic users will be required to modify their usage behaviour in accordance with energy efficiency targets. Clustering allows usage data, collected at the household level, to be clustered into groups and assigned a stereotypical profile which may be used to provide individually tailored energy plans. Fuzzy C Means extends previous work based around crisp K means clustering by allowing a household to be a member of multiple customer profile groups to different degrees, thus providing 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 household’s changing behaviour is moving them towards more ”green ” or cost effective stereotypical usage

Topics: H.4 [Information Systems Applications, Miscellaneous General Terms Algorithms, Economics, Human Factors Keywords Electricity load profiles, Clustering, Fuzzy C Means, Demand Side Management
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.308.1492
Provided by: CiteSeerX
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