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Clustering time-series energy data from smart meters

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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-h 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.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA

    Alexander Lavin & Diego Klabjan

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  1. Alexander Lavin
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  2. Diego Klabjan
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Correspondence to Alexander Lavin.

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Lavin, A., Klabjan, D. Clustering time-series energy data from smart meters. Energy Efficiency 8, 681–689 (2015). https://doi.org/10.1007/s12053-014-9316-0

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  • DOI: https://doi.org/10.1007/s12053-014-9316-0

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