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the inability of traditional meters to identify and measure energy consumption at specific times or, more directly, for specific appliances that have been installed with equipment designed to conserve energy. A modern demand response network with automated metering provides data at short intervals (hourly or less), thereby providing greater temporal resolution with which to conduct accurate M&V in real time. Further, metering equipment used in demand response programs can provide direct or proxy measurement of end-use consumption for space conditioning and water heating, the two largest residential end uses, and those with the most significant seasonal swings that confound the analysis of monthly bills. In commercial buildings, this equipment can provide direct or proxy measurement of the breakdown of HVAC refrigeration, and in some cases lighting, the primary end uses in commercial buildings. Thus, in addition to the increased temporal resolution, demand response networks can also provide highly valuable end-use resolution to improve M&V accuracy at lower cost. Annual M&V costs were once estimated at 3% to 15% of the annual savings associated with the aforementioned benefits (DOE/FEMP 2005). For example, the Texas LoanSTAR (Loans to Save Taxes and Resources) program, which is a statewide capital retrofit program for enhancing energy efficiency in buildings, had (as of November 2007) funded 191 loans valued at more than $240 M. Energy savings resulting from the projects tied to these loans had reached more than $212 M (TSEC 2009). Through October 1999, the M&V costs associated with the Texas LoanSTAR program were computed at 11.5% of total loan value for a five-year program. That amount was computed by adding metering costs of 3.5% of the loan and annual M&V costs of 1.6% over five years (Turner et al. 2000). In recent years, however, more detailed assessments of M&V costs have reduced and narrowed the cost range, and are currently estimated to average 3% of the value of annual savings (Shonder 2009). M&V technologies enhance the political and regulatory landscape for utilities interested in expanding energy efficiency programs tied to the smart grid. To quantify the potential energy savings associated with enhanced M&V capabilities, the Electric Power Research Institute (EPRI) used the findings of a study on the potential of energy efficiency measures in the United States conducted by EPRI and the Edison Electric Institute (EEI). The study, which examined stock turnover to estimate potential energy efficiency gains through 2030, used the EIA Annual Energy Outlook 2007 as the baseline forecast. The analysis yielded a 7% to 11% estimate of potential energy efficiency gains through 2030, equivalent to 398 to 544 B kWh of reduced energy consumption (EPRI 2009). The EPRI/EEI study bounds its estimated energy efficiency savings based on two sets of assumptions, one deemed the realistic achievable potential (7% reduction in baseline electricity consumption) and one identified as the maximum achievable potential (11% reduction in baseline electricity consumption). The maximum achievable potential scenario is based on the results of the most successful energy efficiency programs in the United States while the realistic achievable scenario discounts these results based on factors that could undermine program effectiveness, such as budgetary constraints and energy efficiency learning curves. Using the findings of the EPRI/EEI study, EPRI estimated the potential energy efficiency impact of M&V capabilities enabled by the smart grid. First, EPRI used the range between the realistic achievable potential and maximum achievable potential (146 B kWh) to establish the baseline against which to estimate the impact of M&V capabilities. Second, EPRI assumed that the difference between the two scenarios (realistic achievable potential and maximum achievable potential) would be based on a number D.2PDF Image | The Smart Grid: An Estimation of the Energy and CO2 Benefits
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