Extracting operating modes from building electrical load data

2011 IEEE Green Technologies Conference, Green 2011

Volumn , Issue , 2011, Pages

  Frank, Stephen ^a   Gentile Polese, Luigi ^b   Rader, Emily ^b   Sheppy, Michael ^b   Smith, Jeff ^b  

^a Department of Geology and Geological Engineering   (United States)

^b NATIONAL RENEWABLE ENERGY LABORATORY   (United States)

Author keywords

buildings; clustering; miscellaneous electrical loads; mode extraction; system characterization

Indexed keywords

CLUSTERING; CLUSTERING METHODS; ELECTRICAL ENERGY; ELECTRICAL LOAD; ELECTRICITY-CONSUMPTION; EMPIRICAL TECHNIQUES; ENERGY SAVING; IN-BUILDINGS; MISCELLANEOUS ELECTRICAL LOADS; MODE EXTRACTION; OPERATING MODES; SYSTEM BEHAVIORS; SYSTEM CHARACTERIZATION;

HEURISTIC METHODS; TECHNOLOGY;

ELECTRIC LOADS;

EID: 79956111220     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GREEN.2011.5754872     Document Type: Conference Paper

References (24)

1. K. McKenney, M. Guernsey, R. Ponoum, and J. Rosenfeld, "Commercial miscellaneous electric loads: Energy consumption characterization and savings potential in 2008 by building type." TIAX LLC, Lexington, MA, Tech. Rep. D0498, May 2010, p. 224.
2. D&R International, Ltd., 2009 Buildings Energy Data Book. U.S. Department of Energy, 2009.
3. Energy Information Administration, "Annual Energy Outlook 2009, With Projections to 2030." U.S. Department of Energy, Washington, DC, Govt. Rep. DOE/EIA-0383(2009), March 2009.
4. A. de Almeida, P. Fonseca, B. Schlomann, N. Feilberg, and C. Ferreira, "Residential monitoring to decrease energy use and carbon emissions in Europe," in Proceedings of the 4th International Conference on Energy Efficiency in Domestic Appliances and Lighting, London, United Kingdom, 2006, vol. 2, pp. 529-544.
5. L. Moorefield, B. Frazer, and P. Bendt, "Office plug load field monitoring report." Ecos, Durango, CO, White Paper, Dec. 2008.
6. C. Cremer et al., "Energy Consumption of Information and Communication Technology (ICT) in Germany up to 2010." Fraunhofer ISI and Centre for Energy Policy and Economics, Karlsruhe/Zurich, White Paper, Jan. 2003.
7. J. A. Roberson, C. A. Webber, M. C. McWhinney, R. E. Brown, M. J. Pinckard, and J. F. Busch, "After-hours Power Status of Office Equipment and\line Energy Use of Miscellaneous Plug-Load Equipment." Lawrence Berkeley National Laboratory, Berkeley, CA, Tech. Rep. LBNL-53729, May 2004.
8. Household Electrical Appliances - Measurement of Standby Power, IEC Standard 62301, 2005.
9. G. W. Hart, "Nonintrusive appliance load monitoring," Proceedings of the IEEE, vol. 80, no. 12, pp. 1870-1891, 1992.
10. M. Baranski and J. Voss, "Genetic algorithm for pattern detection in NIALM systems," in Proceedings of the 2004 IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 3462-3468.
11. A. Marchiori and Q. Han, "Using circuit-level power measurements in household energy management systems," presented at the First ACM Workshop On Embedded Sensing Systems For Energy-Efficiency In Buildings (BuildSys), Berkeley, CA, 2009.
12. C. Laughman et al., "Power signature analysis," IEEE Power and Energy Magazine, vol. 1, no. 2, pp. 56-63, 2003.
13. K. D. Lee, S. B. Leeb, L. K. Norford, P. R. Armstrong, J. Holloway, and S. R. Shaw, "Estimation of Variable-Speed-Drive Power Consumption From Harmonic Content," IEEE Transactions on Energy Conversion, vol. 20, pp. 566-574, Sep. 2005. (Pubitemid 41269630)
14. L. K. Norford, S. B. Leeb, D. Luo, and S. R. Shaw, "Advanced electrical load monitoring: a wealth of information at low cost." presented at Diagnostics for Commercial Buildings: from Research to Practice, Pacific Energy Institute, San Francisco, CA, 1999.
15. K. Roth, "Review of techniques for non-intrusive electrical load monitoring," Seminar, 13-Aug-2010. [Online]. Available: http://eetdseminars.lbl.gov/seminar/review-techniques-non-intrusive- electricalload-monitoring
16. R. Xu and D. Wunsch, Clustering. Hoboken, NJ: John Wiley & Sons, 2009.
17. P. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining, US ed. Reading, MA: Addison-Wesley, 2005.
18. M. Ester, H. Kriegel, J. Sander, and X. Xu, "A density-based algorithm for discovering clusters in large spatial databases with noise," in Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining, 1996, pp. 226-231.
19. C. Fraley and A. E. Raftery, "Model-based clustering, discriminant analysis and density estimation," Journal of the American Statistical Association, vol. 97, pp. 611-631, 2002.
20. J. Sander, M. Ester, H. Kriegel, and X. Xu, "Density-based clustering in spatial databases: The algorithm GDBSCAN and its applications," Data Mining and Knowledge Discovery, vol. 2, pp. 169-194, 1998.
21. M. Ankerst, M. M. Breunig, H. Kriegel, and J. Sander, "OPTICS: Ordering points to identify the clustering structure," SIGMOD Record, vol. 28, no. 2, pp. 49-60, 1999. (Pubitemid 129597323)
22. R Development Core Team, R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, 2010.
23. C. Fraley and A. E. Raftery, "MCLUST version 3 for R: Normal mixture modeling and model-based clustering." Dept. of Statistics, University of Washington, Seattle, WA, Tech. Rep. 504, Sep. 2006.
24. C. Hennig, fpc: Fixed point clusters, clusterwise regression and discriminant plots. [Online.] Available: http://CRAN.R-project.org/package=fpc