Low residential energy use is typically associated with undesirable characteristics, such as poverty, thermal discomfort, or small dwelling size. The association of low energy use with deprivation has been an obstacle to promoting more aggressive goals for reduction of residential use. However, there is little research on the composition of the low user population. We investigated the demographics, behavior, and satisfaction of the lowest 10% of electricity consumers in Sacramento, CA, to see what attributes best correlated with low use. California, like many other regions, has GHG emissions goals requiring drastic reductions in residential consumption. Households in Sacramento’s lowest decile of electricity consumption already live at electricity consumption levels consistent with the goals for 2050. Our investigation of 700 of these households found that diversity of low users with regard to age, income, education, appliance ownership, and dwelling characteristics is similar to that of the general population. Low-use households tend to be smaller, but not enough to explain the entirety of low usage. Surveys and interviews revealed that those in the lowest 10% typically pursued low consumption deliberately and enthusiastically and were aware of their status as low users. Conversations about energy conserving strategies were embedded in their social lives. They employed diverse and creative strategies to maintain thermal comfort without excess energy use, often exceeding expert recommendations. Finally, the distribution of self-reported quality of life was no different from that of the general population living at much higher consumption levels. Overall, the key determinants of low use were a positive engagement with improvisation and experimentation, and the salience of energy in personal or social life. The population of low users should be treated as a valuable source of peer advice and lifestyle modeling.
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See http://gainesvillegreen.com/. The opposite effect, i.e. provoking an increase in consumption by lower-use households, is of course also possible.
The full report is Reuben Deumling et al. (2013): “Identifying Determinants of Very Low Energy Consumption Rates Observed in Some California Households”. Available at https://www.arb.ca.gov/research/apr/past/09-326.pdf .
Deumling et al. (2013), p. 7, Figures 5.1 and 5.2. Monthly usage for the overall population ranged from 50 to 1850 kWh/month. The boundary of the lowest decile lay at about 330 kWh/month.
For regression table see Deumling et al. (2013), pp. 77–73; for survey questions pp. 76–83; for interview template pp. 84–85.
For the sole purpose of the regression analysis, we compared the lowest quartile (rather than decile) of electricity customers with the general population of the SMUD service area. In contrast to the rest of the study, the goal here was to establish linear relationships between electricity usage and the variables of interest; thus, the use of the somewhat broader data set was preferable. Results from regression models are presented in Deumling et al. (2013), pp. 72–73, Table A.1.
Deumling et al. (2013), p.19, Figure 6.9.
Deumling et al. (2013), p. 17, Figure 6.6. We further compared the lowest decile with the general population as to age distribution (Figures 6.3, 6.7, and 6.8) educational attainment of household head (Figure 6.2), and ethnicity (Figure 6.4).
Deumling et al. (2013), pp. 23 ff, and Survey Questions 7 and 18.
Here and in all subsequent mention of survey questions, the document is reproduced in Deumling et al. (2013), pp. 76–83.
Deumling et al. (2013), p. 38, Figure 6.24.
Deumling et al. (2013), p. 41, Figure 6.27. Even respondents who did not believe their energy use to be lower (or their home less cooled) than that of their neighbors may still have recognized themselves as low users: given that our pool was a full 10% of the population, their neighbors could also have been low users.
Deumling et al. (2013), p. 27, Figure 6.21.
Deumling et al. (2013), p. 28, Figure 6.22.
Some respondents mentioned both constraints and voluntary pursuit of low use.
Deumling et al. (2013), pp. 39–40 and pp. 80–81 (Survey Questions 25–27).
There have been some efforts to leverage social media to target energy reduction messages more effectively. Dougherty et al. (2011) describe data-driven social norm messaging programs that target high users through information mailed to customers, including a usage comparison across demographically similar households and a series of recommended actions. Seattle City Light has studied variation among their residential customers, as well as high usage, as a way to identify opportunities for large savings (2010, also Meier 2010). An outreach campaign by the Gainesville [Florida] Regional Utility puts customer usage information on a searchable public website “to enable us all to make better decisions about our energy usage” (Gainesville Green n.d.). Although these give the appearance of targeted outreach tailored to market niches, in fact the same behavioral strategy is deployed for the entire audience. At the other end of the usage spectrum, subsidy or assistance programs are aimed at a narrow market niche (low income consumers), but these are a form of support rather than an effort to change behaviors.
Deumling et al. (2013), p. 58, Figure 7.6.
For further explanation of the unhappily low energy estimate, see Deumling et al. (2013), pp. 62–64.
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The authors thank the California Air Resources Board for their support.
The research for this study was funded by California Air Resources Board Contract # 09–326.
Conflict of interest
The authors declare that they have no conflict of interest.
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Deumling, R., Poskanzer, D. & Meier, A. “Everyone has a peer in the low user tier”: the diversity of low residential energy users. Energy Efficiency 12, 245–259 (2019). https://doi.org/10.1007/s12053-018-9703-z
- Household energy consumption
- Residential energy demand
- Energy behavior
- Energy poverty
- Peer communication