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A third methodological issue concerns the sample size and variability of the studies. In general, the samples were limited to several hundred households, which were as homogeneous as possible within the research design. It is an open question as to what the conservation and efficiency potential is for a much wider range of domestic arrangements. Household composition has been shown to be a significant predictor of energy use, but much less is known about conservation and efficiency potential. It has been shown that larger effects are obtained for high versus low consumers, with some potential for rebound at the low end of usage. Large-scale smart grid/metering implementation plans will cover a much greater range of domestic arrangements, and it will be important to evaluate conservation and efficiency effects in terms of a domestic segmentation analysis. A final methodological issue relates to the behavioral granularity of the conservation and efficiency effects reported. While it is known that savings occur, how the savings were actually achieved is not clear because structured debriefings or household task analyses were not a routine part of many of the studies. There is considerable room in new research to address the question of: “what is happening behaviorally behind the meter?” A variety of surveys provides suggestions for implementing and gathering information on those actions that are easiest for consumers to execute and would yield consistent savings (Woods 2008; Secrest 2005). Addressing behavioral specificity would be a natural part of any large-scale implementation and would be a fundamental part of evaluating long-term savings, or lack thereof. A number of additional issues pertinent to consumer behavior are worthy of consideration in future field research. They might be part of a large-scale study, follow-up analyses to work already performed, or potentially surveys that are aimed at better understanding likely savings effects and behavioral “entry points” for various groups of consumers. Among the issues to be addressed are: • The role of habit, behavior change, and cognitive control. Cognitive psychology offers concepts and theories suggesting that conservation behavior is a new habit requiring skill learning. Incorporating approaches from cognitive behavior modification and human factors engineering into smart meter implementations could entail such manipulations as a pay-as-you-go system, which has been shown to be successful in Northern Ireland (Darby 2006). The meter commands attention, and ultimately financial resources, and would assist the end user in developing alternative energy-use habits. • Conduct research into consumer mental models of energy–how do people think about energy? Do they think about it (other than gasoline?). Stern and Aronson (1984) proposed that over a 100-year period, people have become “energy unaware” to the point that much household usage is “invisible.” System transparency is a fundamental concept in human factors engineering for complex systems, and may have some application in this area. • In field research on interventions, it is possible to increase the time granularity of data to better understand energy usage patterns across the 24-hour period, weekly and weekend differences, and variations within time periods of the seasons. More granular data can help to identify recurring behaviors that are targets for modification. • Develop more specific guidelines for information and outreach programs that are directly linked to social psychological findings, but are abstracted out of the numerous review papers and presented in a format that makes “best practices” more accessible to energy utilities that may want to implement a program. A.5PDF Image | The Smart Grid: An Estimation of the Energy and CO2 Benefits
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