Reflecting energy use patterns and lifestyles in home using data mining techniques

Niloufar Kioumarsi, Julian Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most methods to analyse and understand the residential energy use features rely on invasive measurements, such as energy monitoring systems, which eventually affects the reliability of pattern classifications. This paper, thus, adopts a non-invasive method using unsupervised data mining algorithms to analyse hourly energy consumption data in order to learn the occupant's lifestyle and energy consumption behavioral patterns. The study analyses hourly energy use of 298 households in Texas in 2015, using an online open source data set - Pecan Street Dataport. This study scientifically identified household's energy use features and associated behavioural patterns through a multi scale observation of the clusters. As the contribution, this study takes the house age and size into account as these variables may significantly affect building energy use patterns. Second, it takes dissimilarity measures into account by using TSclust R package for clustering time series. And third, introduces a method of multiscale observation of clusters in order to interpret the lifestyle patterns. Finally, the results demonstrated how data mining techniques might be utilized to help investigating energy use data from the behavioural perspective.

Original languageEnglish (US)
Title of host publicationPLEA 2018 - Smart and Healthy within the Two-Degree Limit
Subtitle of host publicationProceedings of the 34th International Conference on Passive and Low Energy Architecture
EditorsEdward Ng, Square Fong, Chao Ren
PublisherSchool of Architecture, The Chinese University of Hong Kong
Pages1071-1073
Number of pages3
ISBN (Electronic)9789628272365
StatePublished - 2018
Event34th International Conference on Passive and Low Energy Architecture: Smart and Healthy Within the Two-Degree Limit, PLEA 2018 - Hong Kong, China
Duration: Dec 10 2018Dec 12 2018

Publication series

NamePLEA 2018 - Smart and Healthy within the Two-Degree Limit: Proceedings of the 34th International Conference on Passive and Low Energy Architecture
Volume3

Conference

Conference34th International Conference on Passive and Low Energy Architecture: Smart and Healthy Within the Two-Degree Limit, PLEA 2018
Country/TerritoryChina
CityHong Kong
Period12/10/1812/12/18

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

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