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change their energy consumption behavior in response to feedback, and that the conditions surrounding feedback, such as frequency and specificity, are influential variables. This implies that a smart grid/metering system may yield considerable savings in terms of end-use conservation, with a basic goal of time-of-use load shifting. Feedback tends to be most effective when it: • is based on actual usage data • is provided on a frequent basis (daily is better than weekly, etc.) • involves goal setting and choice • is provided over a year or more • involves specific behavioral recommendations regarding appliances • involves normative or historical comparisons. Fischer (2008) contends that these items favor the smart grid capabilities offered by AMI and two- way communication networks, which provide an effective way of engaging the consumer and providing tailored feedback. The energy-use reductions achieved from a range of projects examined by Fischer (2008) range from 5% to 20%, with a median of approximately 6%. Similar results have been observed in utility field studies reviewed by Faruqui et al. (2009). We have adopted this estimate of the potential. The key issue surrounding these results is whether they are sustainable over a time period of years and decades. Given that consumers generally volunteer for such studies, there may be some built-in bias up front. More importantly, does the consumer continue to seek out feedback, or internalize it and translate that into permanent changes in behavior? To be conservative, we have shifted the range of uncertainty lower, to a low of 1% and a high of 10%. We assume that, with respect to the contribution of a smart grid, a direct reduction of 6% in electricity consumption only for the residential and small/medium commercial building sectors. At a minimum, such a feedback mechanism requires an interval meter that is fundamental to a smart grid. Large commercial buildings and industrial customers generally already have such meters, and consume enough energy to install relatively sophisticated feedback systems and pay a staff member to monitor energy use, so it is difficult to assert that a smart grid is essential to achieving similar savings in this customer class. Quite substantial potential reductions of 3% in electricity consumption and associated CO2 emissions are estimated in Table 3.3, with the calculations documented in Attachment 2. No indirect reductions from capital or cost savings are expected. Table 3.3. Estimated Direct Impacts of the Conservation Effect of Consumer Information and Feedback Systems Reduced Energy Consumption (2030) Baseline Electricity Consumption Electric Sector Annual Reductions (2030) Est. % 6 6 Low High % % 1 10 1 10 End-Use Sector(s) Residential (10 9 kWh/year) 1722 854 % of United States Carbon Emissions % of United (MMT/ Energy 9 (10 kWh/ year) 3 155 3 92 States yearr) Small/Medium Commercial Buildings 3.9PDF Image | The Smart Grid: An Estimation of the Energy and CO2 Benefits
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