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Clustering Time-Series Energy Data from Smart Meters

Machine Learning 2016-03-25 v1
Authors: Alexander Lavin , Diego Klabjan
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Abstract

Investigations have been performed into using clustering methods in data mining time-series data from smart meters. The problem is to identify patterns and trends in energy usage profiles of commercial and industrial customers over 24-hour periods, and group similar profiles. We tested our method on energy usage data provided by several U.S. power utilities. The results show accurate grouping of accounts similar in their energy usage patterns, and potential for the method to be utilized in energy efficiency programs.

Keywords

clustering weather forecasting

Cite

@article{arxiv.1603.07602,
  title  = {Clustering Time-Series Energy Data from Smart Meters},
  author = {Alexander Lavin and Diego Klabjan},
  journal= {arXiv preprint arXiv:1603.07602},
  year   = {2016}
}

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