Utility customer segmentation based on smart meter data: Empirical study

2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013

Volumn , Issue , 2013, Pages 720-725

  Kwac, Jungsuk ^a   Tan, Chin Woo ^a   Sintov, Nicole ^b   Flora, June ^a   Rajagopal, Ram ^a  

^a STANFORD UNIVERSITY   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATED DATUM; CUSTOMER SEGMENTATION; CUSTOMER SEGMENTS; EMPIRICAL STUDIES; ENERGY INFORMATION; HOUSEHOLD ELECTRICITY CONSUMPTION; STATISTICAL PROPERTIES; STATISTICAL TECHNIQUES;

SALES;

SMART POWER GRIDS;

EID: 84893585042     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SmartGridComm.2013.6688044     Document Type: Conference Paper

References (12)

1. B. Sutterlin, T.A. Brunner, and M. Siegrist, "Who puts the most energy into energy conservation? A segmentation of energy consumers based on energy-related behavioral characteristics", Energy Policy, Vol. 39, pp. 8137-8152, 2011.
2. T.F. Sanquist, H. Orr, B. Shui, and A.C. Bittner, "Lifestyle factors in U.S. residential electricity consumption", Energy Policy, Vol. 42, pp. 354-364, 2012.
3. A. Diamantopoulos, B.B. Schlegelmilch, R.R. Sinkovics, G.M. Bohlen, "Can socio-demographics still play a role in profiling green consumers? A review of the evidence and an empirical investigation", Journal of Business Research, Vol. 56, No. 6, pp. 465-480, 2003.
4. W. Abrahamse, L. Steg, "How do socio-demographic and psychological factors relate to households' direct and indirect energy use & savings?", Journal of Economic Psychology, Vol 30, pp. 711-720, 2009.
5. π, Proceedings of IEEE International Conference on Smart Grid Communications, pp. 7-12, 17-20 October, 2011.
6. G.W. Irwin, W. Monteith, and W.C. Beattie, "Statistical electricity demand modelling from consumer billing data", Proceedings of IEE, Vol. 133, Pt. C, No. 6, September 1986.
7. E.L. Crow amd K. Shimizu, eds, Log-normal Distributions: Theory and Application, New York: Dekker, 1988.
8. J. Kwac, J. Flora, and R. Rajagopal, "Household energy consumption segmentation using hourly data", IEEE Transcations on Smart Grid, accepted for publication.
9. Z. Kolter and J. Ferreira, "A large-Scale study of predicting and contextualizing building energy ssage", Proceedings of the AAAI Conference on Artificial Intelligence, 2011.
10. E. Limpert, W.A. Stahel, and M. Abbt, "Log-normal distributions across the sciences: keys and clues, BioScience, Vol. 51, No. 5, pp. 341-352, May 2011.
11. "2009 California Residential Appliance Saturation Study (RASS)", Report CEC-200-2010-004-ES, prepared by KEMA, Inc. for California Energy Commission, October 2010.
12. S. Bhatia, "Adpative k-means clustering", Proceedings of International Florida Artificial Intelligent Research Society Conference (FLAIRS), pp. 695-699, May 2004.