Performance comparison framework for energy disaggregation systems

Conference Paper

Energy disaggregation algorithms decompose building-level energy data into device-level information. We conduct a head-To-head comparison of energy disaggregation techniques across multiple metrics and data sets. Our framework for analyzing the performance of a complete energy disaggregation system includes event detection, classification, and power assignment. We use receiver operating characteristics (ROCs) to evaluate event detection performance, and we introduce a technique to evaluate device-level event detection. We use confusion matrices to compare classification performance across several classifiers, and evaluate the resulting power assignments using several assignment metrics that are commonly used in the literature to demonstrate the varying strengths of the techniques that were considered. We apply this framework to several publicly available datasets and demonstrate how system performance varies with sampling frequency and the inclusion of reactive power. Our results suggest that (1) disaggregation performance varies considerably across data sets (2) increased data sampling rate improves disaggregation performance, and (3) additional features such as reactive power yields disaggregation performance improvements.

Full Text

Duke Authors

Cited Authors

  • Czarnek, N; Morton, K; Collins, L; Newell, R; Bradbury, K

Published Date

  • March 17, 2016

Published In

  • 2015 Ieee International Conference on Smart Grid Communications, Smartgridcomm 2015

Start / End Page

  • 446 - 452

International Standard Book Number 13 (ISBN-13)

  • 9781467382892

Digital Object Identifier (DOI)

  • 10.1109/SmartGridComm.2015.7436341

Citation Source

  • Scopus