Skip to main content

Currently Skimming:

6. Predicted and Actual Energy Savings from Home Retrofits
Pages 79-91

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 79...
... For example, an electric utility company that is counting on home retrofits to obviate the need for a new power plant must be able to tell 10 years in advance whether its conservation programs will save enough energy to meet that goal and whether programs that meet that goal will cost less than building generating capacity. Regulatory agencies that want utilities to invest in conservation rather than constructing new plants have the same needs.
From page 80...
... Finally, the accuracy of an estimate may deteriorate over time as wall insulation settles, other materials break down, or occupant behavior changes. It makes a difference which of these hypotheses accounts for most of the discrepancy between actual and predicted energy savings, because they have different implications about how to improve prediction.
From page 81...
... For a utility company investing in conservation, one hypothesis suggests that an investment in inspecting contractors' work could bring energy savings into line with expectations; another hypothesis implies that savings predictions should be lowered because they have not taken into account people's behavioral responses to improved energy efficiency. That implication would lead utilities to decrease support for residential conservation if that support was based on expected relief from demand growth.
From page 82...
... If studies proceed one at a time, research should probably begin in an area with heavy heating loads because it may be possible to get reliable determinations of effects with a small sample and even with rather rough measurement techniques . Within each climate zone, a housing market should be chosen for its variety of housing types, contractor types, socioeconomic status among homeowners, and the availabi 1ity of a competent research team.
From page 83...
... All the above information can help tell whether gaps between actual and predicted energy savings are due mainly to estimation models or to actual changes in buildings and their occupants. Reassessment after two and three years is necessary in at least a subsample of homes to examine hypotheses involving deterioration of retrofit materials, slow reversion to old habits of energy use, or behavioral changes that have the effect of using the money the retrofit saved to increase energy consumption in other ways.
From page 84...
... Unlike meter readings or the observaas a direct observation against which to assess the adequacy of regression models of furnace operation based on meter readings. It can reflect and be checked against a range of behaviors, including thermostat talons Rescreen above.
From page 85...
... Other Direct Measures Indoor temperature regulation is the short-term behavioral adjustment with the greatest effect on a home's energy use. Indoor temperature must be monitored to test the frequently asserted hypothesis that people, especially those in low-income households, who have been sacrificing comfort to pay energy bills will respond to improved energy efficiency by resetting thermostats.
From page 86...
... Thus, both thermostat settings and indoor temperatures should be monitored. Hot water use is a major energy variable in homes that is behaviorally controlled: Kempton (1984)
From page 87...
... Second, the need to calculate Tref for each home puts the procedure beyond the capability of inexperienced analysts using standard statistical programs. A simplified system that calculates NAC based on an assumed uniform value of Tref has been developed at Oak Ridge National Laboratory (Berry and Vineyard, 1985~.
From page 88...
... Where space heaters are not metered, survey questions should inventory space heating equipment, get specifications for the equipment if feasible, and ask about the frequency of use for each piece of equipment. To validate regression models of the impact of this equipment when direct measurements cannot be made, it will be useful to conduct surveys during the heating or cooling season and to ask about the use of supplementary heating and cooling during the previous day.
From page 89...
... It is a fairly simple behavioral adaptation that may have important effects on energy bills. It is also easily reversible if energy costs become a less salient problem for households.
From page 90...
... In addition, less than complete instrumentation can generate useful knowledge about some important questions. For example, a study of behavioral changes after retrofitting requires repeated and detailed surveys, but valuable information can be gained with limited instrumentation to assess thermostat settings, indoor temperature, furnace use, and perhaps use of space heaters and hot water.
From page 91...
... 91 understand the causes of the unsatisfying performance of the models and to improve the ability to predict the effect of retrofits requires simultaneous assessment of equipment and human behavior; to make policies that could improve the effectiveness of retrofits will also require attention to both technology and behavior. In this way, the issue of predicted versus actual energy savings underlines the value of the kinds of analysis considered in this report: energy use is a human activity that occurs through technology; to understand it, one must comprehend not only the relevant technologies but also the people who use them.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.