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Variability of Behaviour in Electricity Load Profile Clustering; Who Does Things at the Same Time Each Day?

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Advances in Data Mining. Applications and Theoretical Aspects (ICDM 2014)

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Abstract

UK electricity market changes provide opportunities to alter households’ electricity usage patterns for the benefit of the overall electricity network. Work on clustering similar households has concentrated on daily load profiles and the variability in regular household behaviours has not been considered. Those households with most variability in regular activities may be the most receptive to incentives to change timing. Whether using the variability of regular behaviour allows the creation of more consistent groupings of households is investigated and compared with daily load profile clustering. 204 UK households are analysed to find repeating patterns (motifs). Variability in the time of the motif is used as the basis for clustering households. Different clustering algorithms are assessed by the consistency of the results.

Findings show that variability of behaviour, using motifs, provides more consistent groupings of households across different clustering algorithms and allows for more efficient targeting of behaviour change interventions.

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Dent, I., Craig, T., Aickelin, U., Rodden, T. (2014). Variability of Behaviour in Electricity Load Profile Clustering; Who Does Things at the Same Time Each Day?. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2014. Lecture Notes in Computer Science(), vol 8557. Springer, Cham. https://doi.org/10.1007/978-3-319-08976-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-08976-8_6

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08975-1

  • Online ISBN: 978-3-319-08976-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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