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Energy use of US residential refrigerators and freezers: function derivation based on household and climate characteristics

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Abstract

Field-metered energy use data for 1,467 refrigerators and 185 freezers from seven studies conducted between 1992 and 2010 were used to calculate usage adjustment factors (UAFs), defined as the ratio of measured to tested annual energy use. Multiple regressions of UAFs against several household and climate variables were then performed to obtain separate predictive functions for primary (most-used) refrigerators, secondary (second most-used) refrigerators, and freezers, and residual differences between observed and modeled UAFs were fit to log normal distributions. These UAF functions were used to project energy use in the more than 4,000 households in the 2005 Residential Energy Consumption Survey, a statistical representation of US homes. These energy use projections formed the basis of calculating lifecycle energy savings for more efficient refrigerators and freezers, as well as national energy and cost savings. Results were compared with previous published work by the Department of Energy, demonstrating how UAFs impact energy and cost savings. Such an approach could be further improved with additional data and adapted for other appliances in future analyses.

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Notes

  1. Full citation: Title 10—Energy, Chapter II—Department of Energy, Part 430—Energy Conservation Program for Consumer Products, Subpart B—Test Procedures, Appendix A1

  2. However, Meier (1995) notes that the success of the DOE test may have been largely fortuitous and that future design changes to refrigerators and freezers may require that the ambient temperature or other conditions of the test procedure be changed to better reflect actual average energy use.

  3. New data based on a survey conducted in 2009 became available in late 2011 (EIA 2011), but it was too late to be incorporated here.

  4. We note that there is also an issue of production variability that can affect the TEC. Although for a well-managed manufacturing facility we expect this variability to be small, it is a contributing factor that will add another degree of “noise” to the measured FEC if test data for the specific unit measured are not available, which was the case for all units in our dataset.

  5. FECmodel is defined by \( {\text{UA}}{{\text{F}}_{{{\text int} }}} = {\text{FE}}{{\text{C}}_{\text{model}}}{\text{/TEC}}. \)

  6. This was done since the regression obtained a non-zero offset, shifting the median relative to the observed data.

  7. This definition is equivalent to the one given earlier, since \( {\text{UAF/UA}}{{\text{F}}_{\text{int}}} = \left( {{\text{FEC/TEC}}} \right)/\left( {{\text{FE}}{{\text{C}}_{\text{model}}}{\text{/TEC}}} \right) = {\text{FEC/FE}}{{\text{C}}_{\text{model}}}. \)

  8. This is admittedly a large assumption and one that was noted earlier in the discussion of the possible need for future changes to the DOE test procedure. However, in the absence of a detailed model of how a more efficient refrigerator or freezer would change its response to household and/or climate variables, we felt that assuming a constant UAF for each household was the most straightforward approach to project future energy use.

  9. While the UAF function used in this analysis is identical to that in the Final Rule, the method of calculating NPV savings in the Final Rule differed from that in the NOPR, unrelated to changes in the UAFs. Therefore, in order to make a direct comparison of the effect of the change in UAFs function on the NPV results, the NOPR method was retained here.

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Acknowledgments

The authors wish to thank Robert Van Buskirk (Department of Energy) and Gregory Rosenquist (Lawrence Berkeley National Laboratory) for encouraging Dr. Greenblatt to initially pursue this analysis, to Peter Chan (Lawrence Berkeley National Laboratory) for performing additional NIA runs to produce the results for this paper, and to Andrew Berrisford (BC Hydro), Gregory Dahlhoff (Dahlhoff & Associates), Scott Pigg (Energy Center of Wisconsin), and John Proctor (Proctor Engineering Group) for sharing their field-metered data. We also wish to thank John Cymbalsky (Department of Energy) for sponsoring this analysis under an Appliance Standards contract with Lawrence Berkeley National Laboratory.

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Author notes

  1. Asa Hopkins

    Present address: Vermont Department of Public Service, Burlington, VT, USA

Authors and Affiliations

  1. Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Jeffery Greenblatt, Asa Hopkins & Virginie Letschert

  2. Blasnik Consulting, Boston, MA, USA

    Michael Blasnik

Authors
  1. Jeffery Greenblatt
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  2. Asa Hopkins
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  3. Virginie Letschert
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  4. Michael Blasnik
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Correspondence to Jeffery Greenblatt.

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Greenblatt, J., Hopkins, A., Letschert, V. et al. Energy use of US residential refrigerators and freezers: function derivation based on household and climate characteristics. Energy Efficiency 6, 135–162 (2013). https://doi.org/10.1007/s12053-012-9158-6

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  • DOI: https://doi.org/10.1007/s12053-012-9158-6

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