The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - January-March (2011 vol.10)
pp: 28-39
Jon Froehlich , University of Washington
Eric Larson , University of Washington
Sidhant Gupta , University of Washington
Gabe Cohn , University of Washington
Matthew S. Reynolds , Duke University
Shwetak N. Patel , University of Washington
ABSTRACT
Most energy meters installed by utilities are intended primarily to support billing functions. Meters report only the aggregate energy consumption of a home or business over intervals as long as a month. In contrast, disaggregated energy usage data identified by individual devices or appliances offers a much more descriptive dataset that has the potential to inform and empower a wide variety of energy stakeholders, from homeowners and building operators to utilities and policy makers. In this article, the authors survey existing and emerging disaggregation techniques and highlight signal features that might be used to sense disaggregated data in a viable and cost-effective manner. They provide a summary of a new approach to electrical load disaggregation that uses voltage noise, including a brief overview of their sensing hardware, classification algorithms, and evaluation in 14 homes. The article concludes with a discussion of current open research problems that must be addressed before disaggregated energy sensing can be widely deployed.
INDEX TERMS
Disaggregated energy sensing, Sustainability, Electricity, Water, Gas, Smart grid
CITATION
Jon Froehlich, Eric Larson, Sidhant Gupta, Gabe Cohn, Matthew S. Reynolds, Shwetak N. Patel, "Disaggregated End-Use Energy Sensing for the Smart Grid", IEEE Pervasive Computing, vol.10, no. 1, pp. 28-39, January-March 2011, doi:10.1109/MPRV.2010.74
REFERENCES
1. L.G. Swan and V.I. Ugursal, "Modeling of End-Use Energy Consumption in the Residential Sector: A Review of Modeling Techniques," Renewable and Sustainable Energy Reviews, vol. 13, no. 8, 2009, pp. 1819–1835.
2. C.L. Weber and H.S. Matthews, "Quantifying the Global and Distributional Aspects of American Household Carbon Footprint," Ecological Economics, vol. 66, nos. 2–3, 2008, pp. 379–391.
3. J. Seryak and K. Kissock, "Occupancy and Behavioral Effects on Residential Energy Use," Am. Solar Energy Soc. Solar Conf., Am. Solar Energy Soc., 2003; www.sbse.org/awards/docs/2003Seryak1.pdf .
4. R.H. Socolow ed., "The Twin Rivers Program on Energy Conservation in Housing: Highlights and Conclusions," Saving Energy in the Home: Princeton's Experiments at Twin Rivers, Ballinger Publishing Co., 1978, pp. 2–62.
5. B. Mettler-Meibom and B. Wichmann, "The Influence of Information and Attitudes Toward Energy Conservation on Behavior," Einfluss des Verbraucherverhaltens au den Energiebedarf Privater Haushalte, H. Schaefer ed., Springer-Verlag, 1982.
6. M. Costanzo et al., "Energy Conservation Behavior: The Difficult Path from Information to Action," American Psychologist, vol. 41, no. 5, 1986, pp. 521–528.
7. W. Kempton, and L. Montgomery, "Folk Quantification of Energy," Energy, vol. 7, no. 10, 1982, pp. 817–827.
8. R.A. Winett, M.S. Neale, and H.C. Grier, "The Effects of Self-Monitoring and Feedback on Residential Electricity Consumption: Winter," J. Applied Behavior Analysis, vol. 12, no. 2, 1979, pp. 173–184.
9. E.S. Geller, R.A. Winett, and P.B. Everett, Preserving the Environment: New Strategies for Behavior Change, Pergamon Press, 1982.
10. J. Froehlich, "Promoting Energy Efficient Behaviors in the Home through Feedback: The Role of Human-Computer Interaction," Human Computer Interaction Consortium 2009 Winter Workshop, 2009; ftp://ftp.cs.washington.edu/tr/2009/02/UW-CSE-09-02-01.PDF.
11. J. Froehlich, L. Findlater, and J. Landay, "The Design of Eco-Feedback Technology," Proc. CHI 2010, ACM, 2010, pp. 1999–2008.
12. O. Sidler and P. Waide, "Metering Matters!" Appliance Efficiency, vol. 3, no. 4, 1999.
13. Office of Energy Efficiency of Natural Resources Canada, "2003 Survey of Household Energy Use—Detailed Statistical Report," 2003; http://oee.nrcan.gc.ca/Publications/statistics/ sheu03index.cfm.
14. G.W. Hart, "Nonintrusive Appliance Load Monitoring," Proc. IEEE, IEEE Press, 1992, pp. 1870–1891.
15. C. Laughman et al., "Power Signature Analysis," IEEE Power and Energy Magazine, vol. 1, no. 2, 2003, pp. 56–63.
16. S.N. Patel et al., "At the Flick of a Switch: Detecting and Classifying Unique Electrical Events on the Residential Power Line," Proc. Ubiquitous Computing (UbiComp 07), Springer, 2007, pp. 271–288.
17. S. Gupta, M.S. Reynolds, and S.N. Patel, "ElectriSense: Single-Point Sensing Using EMI for Electrical Event Detection and Classification in the Home," Proc. Ubiquitous Computing (UbiComp), ACM Press, 2010, pp. 139–148.
18. M. Berges et al., "Training Load Monitoring Algorithms on Highly Sub-Metered Home Electricity Consumption Data," Tsinghua Science & Technology, vol. 13, Oct. 2008, pp. 406–411.
19. M. Berges, L. Soibelman, and H.S. Matthews, "Building Commissioning as an Opportunity for Training Non-Intrusive Load Monitoring Algorithms," Proc. 16th Int'l Conf. Innovation in Architecture, Engineering and Construction, 2010; www.marioberges.com/pubs2010_berges_iaec.pdf .
20. M. Roberts and H. Kuhns, "Towards Bridging the Gap between the Smart Grid and Smart Energy Consumption," Proc. 2010 ACEEE Summer Study on Energy Efficiency in Buildings, 2010.
21. S. Drenker and A. Kader, "Nonintrusive Monitoring of Electric Loads," IEEE Magazine on Computer Application in Power, vol. 12, no. 4, Oct. 1999, pp. 47–51.
22. A.I. Cole and A. Albicki, "Algorithm for Non-Intrusive Identification of Residential Appliances," Proc. IEEE Int'l Symp. Circuits and Systems (ISCAS 98), IEEE Press, 1998, pp. 338–341.
23. S.B. Leeb, S.R. Shaw, and J.L. Kirtley Jr.,"Transient Event Detection in Spectral Envelope Estimates for Nonintrusive Load Monitoring," IEEE Trans. Power Delivery, vol. 3, no. 3, 1995, pp. 1200–1210.
24. W.K. Lee et al., "Exploration on Load Signatures," Int'l Conf. Electrical Engineering, 2004; http://citeseerx.ist.psu.edu/viewdocsummary?doi=10.1.1.120.5328 .
25. G. Marubayashi, "Noise Measurements of the Residential Power Line," Proc. Int'l Symp. Power Line Communications and Its Applications, 1997, pp. 104–108.
26. E.K. Howell, "How Switches Produce Electrical Noise," IEEE Trans. Electromagnetic Compatibility, vol. 21, no. 3, 1979, pp. 162–170.
27. P.D. Welch, "The Use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time Averaging over Short, Modified Periodograms," IEEE Trans. Audio and Electroacoustics, vol. 15, no. 2, pp. 70–73.
28. S.N. Patel, S. Gupta, and M. Reynolds, "The Design and Evaluation of an End-User-Deployable Whole House, Contactless Power Consumption Sensor," Proc. CHI 2010, ACM Press, 2010, pp. 2471–2480.
7 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool