Summary of Research Findings
`From the Programmable Thermostat Market
`
`EPA has gathered market and demographic Information from market resources,
`manufacturers, utilities, and other industry groups to analyze market research data and
`to determine areas of improvement in the specification. In speaking with manufacturers,
`EPA has found the conversations to be very fruitful and has raised key issues to be
`addressed within this proposal. Below are some highlights from EPA's preliminary
`research on these key issues.
`
`EPA's research Identified several themes and key qualities that are thought to form the
`basis for a challenging and valuable ENERGY STAR specification. These qualities can
`be summarized as follows:
`An ENERGY STAR qualified programmable thermostat must:
`1) Be differentiated in the marketplace by its performance;
`2) Not sacrifice quality or performance;
`3) Save users on their utility bills regardless of different geographic regions and
`dwelling types;
`4) Be cost-effective to recover their investment in a reasonable time period;
`5) Not specify specific technologies to implement features and;
`6) Levels that can be measured and verified with testing.
`
`Programmable Thermostats Offer Untapped Potential
`According to the Energy Information Administration (EIA), energy costs for heating and
`cooling together comprise about 42% of consumer home energy expenditures, on
`average. Yet much of this energy expenditure seems to be used for space conditioning
`during times that the home is unoccupied or occupants are sleeping. Therefore, these
`"unoccupied" periods represent an often-untapped opportunity for reducing home
`energy consumption. Twenty-five million households currently have a programmable
`thermostat. To date, 91 million households use thermostats for their home heating, and
`many of these households offer a market opportunity for programmable thermostats.
`Sales of programmable thermostats have doubled in the last 10 years. With this
`increase in market penetration comes the need to address consumer usability issues to
`aid in future potential energy savings for consumers.
`
`Demographics
`Through its research, EPA has found that among households using thermostats for
`heating, it is estimated that about half of all households (49%) usually do not have
`someone home during the day.1 However, during the winter, less than half (42%) of
`households report turning the heat down and only 2% completely turn the heat off. A
`slightly higher percentag~ of households reported turning the heat down (46%) or off
`(6%) during sleep hours. 11 The question remains as to why such a large proportion of
`households do not appear to be adjusting their thermostats according to occupancy.
`EPA has identified several striking demographic patterns in reported setback practices.
`
`Page 1
`
`ENERGY STAR for Programmable Thermostats
`Definitions
`
`EXHIBIT 2008
`
`1
`
`

`

`For example, Californians turn back their heat at a more substantial setback than the
`national average and those in the coldest regions turn back their heat at lower rates
`than the national average. Further analysis of these patterns and underlying behavior
`may provide valuable insight to consumer practices and the potential for modifying
`these patterns.
`
`Savings Estimates
`Consumers are often advised that installing a programmable thermostat can save them
`anywhere from 1 0 to 30% on the space heating and cooling portion of their energy bills.
`While reliant on proper use of the programmable thermostat, such savings are easily
`true in theory; however, there needs to be more field-tested data to better substantiate
`savings claims. Analyses from recent field studies have suggested that programmable
`thermostats may be achieving considerably lower savings than their estimated potential.
`In particular, a study from the Energy Center of Wisconsin showed no statistical
`difference in heating intensity among their sample of single-family houses when
`comparing households with programmable thermostats and those without. These
`studies suggest that, in practice, programmable thermostats may often not be saving
`the 10%-30% as claimed. However, findings from the Wisconsin study are not
`conclusive and the research itself has some shortcomings (e.g., consumers were using
`an older generation of programmable thermostats). A variety of statistical and
`anecdotal evidence indicates possible reasons as to why discrepancies between
`predicted and actual savings may exist. In particular:
`
`1) Many households (perhaps 30% or highe~11) with programmable thermostats may be
`unable, unwilling, afraid,IV uninterested, or otherwise reluctant to deploy default
`programs or to create or deploy custom programs;
`2) Many households (about 50%v) set back or set up their thermostats manually, thus
`leaving less savings possibilities to be garnered by a programmable thermostat;
`3) The automatic program used with the thermostat may not be any more conservative
`than use of manual thermostats setback or setup by hand;
`4) Many consumers have mental modelsv1 of heating and cooling that lead them to
`believe they will not save energy from setting up or setting back other than long
`periods of time.
`
`By better understanding and addressing these issues, manufacturers may be able to
`increase customer satisfaction and market share, while legitimately claiming substantial
`savings achievable from using programmable thermostats as prescribed.
`
`1 This n11e varied modestly across census division and house type; larger variations arc found amongst various dcmogn1phic groups, in prcdictnblc
`ways (e 11-o niles arc somewhat lower, about 33%, for low-income households and households with older householders).
`11 BllSCd on 1997 RECS.
`;;; This estimate is based on four sources: preliminary 200 I RECS datn; LBNL analysis of 1997 RECS do Ill using adjustments to corrctt for
`apparent over-reponing of presence of progn~mmable thcrmoslllts; o repon by Decision Analysts, Inc.; the aforementioned study by Pigg &
`Nevius (2000). The RECS data, at least, is sclf·reponed, and none of this survey datn can provide much guidance on consistency of use or
`accuracy of reponed use for any case. That is, real consumer thcrmostot usc and tcmpen~ture set point patterns may often be far more complcll.
`thon con be captured in one or 11 few questions on 11 survey.
`" Sec, for ell.ample, Nevius & Pigg (2000), "Progn~mmablc Thermostats That Go Berserk: Taking a Sociol Perspective on Space Heating in
`Wisconsin." Proceedings of the 2000 ACEEE Summer Study on Energy Efficiency In Buildings: Woshington DC, pg. 8.233·8.244.
`
`Page2
`
`ENERGY STAR for Programmable Thermostats
`Definitions
`
`2
`
`

`

`• As the Energy Center of Wisconsin study suggesu, the installation of a prograrnmllblc thcnnoSIIIt does not lnlnslote into more conservative
`thennoSIIIl management regimes.
`'Willett Kempton. 1986. "Homeowner's Models of the Heating System and Hcat Loss Effects on Home Encr&Y Monogcmcnt." Proceedings of the
`1986 ACEEE Summer Study on Energy Efficiency in Buildinas. American Council for on Energy Efficient Economy. Washington DC. Volume
`7. pp. 134-145.
`
`,; As the Energy Center of Wisconsin study suggests, the instollotion of a proarommable thermostot does not lnlnslote to more conservative
`thennostot management regimes.
`•iwiJictt Kempton. 1986. "Homeowner's Models ofthe Heating System and Heat Loss Effects on Home Energy Management." Proceedings of
`the 1986 ACEEE Summcr Study on Ener&Y Efficiency in Buildings. American Council for on EneraY Efficient Economy. Washington DC.
`Volume 7, pp. 134-145.
`
`Page 3
`
`ENERGY STAR for Programmable Thermostats
`Definitions
`
`3
`
`