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fault detection and diagnostics, automate commissioning, enable price-based controls, and enable coordination and integration with other systems. 5.1.3 Joint Marketing of Energy Efficiency and Demand Response Programs The issue is that customers are often confused by the differentiation between energy efficiency and demand response programs; combining the administration of these two types of programs would improve their effectiveness by eliminating the confusion and provide cost savings that could be reinvested in energy efficiency programs. This issue is not addressed in the literature and program data is not in the form that permits estimation of administrative cost reductions or increases in program effectiveness. The recommendation is to assess the impact of co-administering energy efficiency and demand response programs to determine the magnitude of reductions in administrative costs, energy efficiency, and demand response when the programs are administered together. This would enable extrapolation of how the implementation of smart grid technologies may influence the effectiveness (e.g., energy, capacity, and utility cost) of merging energy efficiency and demand response administrative/delivery structures. 5.1.4 Measurement & Verification for Energy Efficiency Programs The issue is that M&V program evaluations of program effectiveness and technology performance are often limited by budget constraints, which lead to reductions in the scope and duration of the effort, as well as the methods used, and which decreases accuracy and transparency. The recommendation is to develop software-based analytic methods that leverage the smart grid’s metering and communication abilities to expand the sample size, improve data granularity, and increase the duration of M&V efforts. This will provide for increased accuracy and transparency, lower cost, and assessment of persistence. 5.1.5 Shifting Load to More Efficient Generation The issue is that estimation of reductions in energy and CO2 emissions is subject to significant uncertainty due to the types of power plants that provide base, intermediate, peak load power, and the order for dispatch. It is recommended that the estimates of energy and CO2 reductions that result from load shift be the subject of more methodical efforts to determine differences that may result by minimizing economic impacts, maximizing energy reductions, and maximizing CO2 reductions. 5.1.6 Support Additional Electric Vehicles and Plug-In Hybrid Electric Vehicles The issue is that analyses to date provide considerable uncertainty for the reduction in CO2 emission due to the high dependency on the reference vehicle to which a PHEV or EV is compared, and the timing and duration of the charging influence on the carbon intensity. In addition, analyses do not provide a uniform estimate of the economic benefits of off-peak-load charging by utilizing higher efficient intermediate or base-load power plants. It is recommended to employ a more comprehensive analysis that analyzes the incremental energy, economic, and environmental benefits of load-management strategies of a growing EV fleet. 5.2PDF Image | The Smart Grid: An Estimation of the Energy and CO2 Benefits
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