4.7 Article

Household Energy Consumption Segmentation Using Hourly Data

Journal

IEEE TRANSACTIONS ON SMART GRID
Volume 5, Issue 1, Pages 420-430

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2013.2278477

Keywords

Clustering; demand response; segmentation; smart meter data; variability

Funding

  1. Department of Energy ARPA-E [DE-AR0000018]
  2. California Energy Commission [PIR-10-054]
  3. Precourt Energy Efficiency Center
  4. TomKat center [1149360-1-WPTAI]
  5. Powell Foundation

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The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

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