Application of a clustering framework to UK domestic electricity data

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Dent, Ian, Aickelin, Uwe and Rodden, Tom Application of a clustering framework to UK domestic electricity data. In: UKCI 2011, the 11th Annual Workshop on Computational Intelligence, 2011, Manchester. (Unpublished)

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Abstract

Abstract—The UK electricity industry will shortly have

available a massively increased amount of data from domestic

households and this paper is a step towards deriving useful

information from non intrusive household level monitoring of

electricity. The paper takes an approach to clustering domestic load profiles that has been successfully used in Portugal and applies it to UK data. It is found that the preferred technique in the Portuguese work (a process combining Self Organised Maps and Kmeans) is not appropriate for the UK data. The workuses data collected in Milton Keynes around 1990 and shows that clusters of households can be identified demonstrating the appropriateness of defining more stereotypical electricity usagepatterns than the two load profiles currently published by the electricity industry. The work is part of a wider project to successfully apply demand side management techniques to gain benefits across the whole electricity network.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/1026057
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 17 Jun 2013 14:45
Last Modified: 04 May 2020 20:34
URI: https://eprints.nottingham.ac.uk/id/eprint/2021

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