Published March 2012 | Version v1
Journal article

Lifestyle factors in U.S. residential electricity consumption

  • 1. Pacific Northwest National Laboratory, Battelle Seattle Research Center, 1100 Dexter Ave., Suite 400, Seattle, WA 98109 (United States)
  • 2. Pacific Northwest National Laboratory, 1000 NE Circle Boulevard, Suite 11101, Corvallis, OR 97330 (United States)
  • 3. Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740 (United States)
  • 4. Bittner and Associates, 13839 S.E. 260th St. Kent, WA 98042 (United States)

Description

A multivariate statistical approach to lifestyle analysis of residential electricity consumption is described and illustrated. Factor analysis of selected variables from the 2005 U.S. Residential Energy Consumption Survey (RECS) identified five lifestyle factors reflecting social and behavioral patterns associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use. These factors were also estimated for 2001 RECS data. Multiple regression analysis using the lifestyle factors yields solutions accounting for approximately 40% of the variance in electricity consumption for both years. By adding the household and market characteristics of income, local electricity price and access to natural gas, variance accounted for is increased to approximately 54%. Income contributed ∼1% unique variance to the models, indicating that lifestyle factors reflecting social and behavioral patterns better account for consumption differences than income. Geographic segmentation of factor scores shows distinct clusters of consumption and lifestyle factors, particularly in suburban locations. The implications for tailored policy and planning interventions are discussed in relation to lifestyle issues. - Highlights: ► Illustrates lifestyle analysis of residential electricity consumption. ► Lifestyle factors based on social and behavioral decisions and equipment use. ► Regression models using lifestyle factors account for 40% of consumption variance. ► Lifestyle factors are stable over time when applied to other data sets. ► Energy reduction opportunities are identified by segmentation analysis.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enpol.2011.11.092

Additional details

Identifiers

DOI
10.1016/j.enpol.2011.11.092;
PII
S0301-4215(11)00990-6;

Publishing Information

Journal Title
Energy Policy
Journal Volume
42
Journal Page Range
p. 354-364
ISSN
0301-4215
CODEN
ENPYAC

Optional Information

Copyright
Copyright (c) 2011 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.