Creating personalised energy plans: from groups to individuals using Fuzzy C Means Clustering

Dent, Ian; Wagner, Christian; Aickelin, Uwe; Rodden, Tom

Abstract

Changes in the UK electricity market mean that domestic
users will be required to modify their usage behaviour in
accordance with energy eciency targets. Clustering allows
usage data, collected at the household level, to be clustered
into groups and assigned a stereotypical prole 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 multi-
ple customer prole groups to dierent degrees, thus provid-
ing the opportunity to make personalised oers to the house-
hold 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 eective stereotypical usage.

Citation

Dent, I., Wagner, C., Aickelin, U., & Rodden, T. Creating personalised energy plans: from groups to individuals using Fuzzy C Means Clustering.

• Conference Name: Digital Engagement 11
• Deposit Date: Jun 17, 2013
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/1026069
• Publisher URL: http://de2011.computing.dundee.ac.uk/wp-content/uploads/2011/10/Creating-Personalised-Energy-Plans-From-Groups-to-Individuals-using-Fuzzy-C-Means-Clustering.pdf