Team for Research in
Ubiquitous Secure Technology

Citation
Roy Dong. "A Dynamical Systems Approach to Energy Disaggregation". Talk or presentation, 9, October, 2013.

Abstract
Energy disaggregation, also known as nonintrusive load monitoring (NILM), is the task of separating aggregate energy data for a whole building into the energy data for individual appliances. Studies have shown that simply providing disaggregated data to the consumer improves energy consumption behavior. However, placing individual sensors on every device in a home is not presently a practical solution. Disaggregation provides a feasible method for providing energy usage behavior data to the consumer which utilizes currently existing infrastructure. In this paper, we present a novel framework to perform the energy disaggregation task. We model each individual device as a single-input, single-output system, where the output is the power consumed by the device and the input is the device usage. In this framework, the task of disaggregation translates into finding inputs for each device that generates our observed power consumption. We describe an implementation of this framework, and show its results on simulated data as well as data from a small-scale experiment.

Electronic downloads

• Dong_TRUST2013.pdf · application/pdf · 5842 kbytes

• HTML

  Roy Dong. <a
  href="http://www.truststc.org/pubs/912.html"
  ><i>A Dynamical Systems Approach to Energy
  Disaggregation</i></a>, Talk or presentation, 
  9, October, 2013.

• Plain text

  Roy Dong. "A Dynamical Systems Approach to Energy
  Disaggregation". Talk or presentation,  9, October,
  2013.

• BibTeX

  @presentation{Dong13_DynamicalSystemsApproachToEnergyDisaggregation,
      author = {Roy Dong},
      title = {A Dynamical Systems Approach to Energy
                Disaggregation},
      day = {9},
      month = {October},
      year = {2013},
      abstract = {Energy disaggregation, also known as nonintrusive
                load monitoring (NILM), is the task of separating
                aggregate energy data for a whole building into
                the energy data for individual appliances. Studies
                have shown that simply providing disaggregated
                data to the consumer improves energy consumption
                behavior. However, placing individual sensors on
                every device in a home is not presently a
                practical solution. Disaggregation provides a
                feasible method for providing energy usage
                behavior data to the consumer which utilizes
                currently existing infrastructure. In this paper,
                we present a novel framework to perform the energy
                disaggregation task. We model each individual
                device as a single-input, single-output system,
                where the output is the power consumed by the
                device and the input is the device usage. In this
                framework, the task of disaggregation translates
                into finding inputs for each device that generates
                our observed power consumption. We describe an
                implementation of this framework, and show its
                results on simulated data as well as data from a
                small-scale experiment.},
      URL = {http://www.truststc.org/pubs/912.html}
  }
  

Posted by Carolyn Winter on 13 Nov 2013.
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