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considers the entire energy conversion path from the extraction of primary energy to the final conversion into useful end-use energy (VMTs in this case). The energy and carbon benefits of smart grid technology applied to EVs reflect, then, the degree to which we can utilize the efficiency improvements associated with the fuel and motor substitution process. In an unmanaged EV charging scenario, the size of the EV fleet that can be supported by the existing grid will be limited or smaller when compared to the EV fleet applying smart grid load control technologies. The smart grid energy and carbon benefits are then estimated as the difference in the improvements between a larger EV fleet (requiring smart grid technology) and a smaller fleet (left unmanaged). It should be clearly noted that this simplified approach will only credit smart grid benefits until the EV fleet size reaches its limit set by unmanaged charging. As will be discussed below, that limit is fairly high, meaning that the grid can accommodate many millions of EVs and PHEVs at the national level without load-management strategies. This simplified approach neglects the economic benefits of off-peak-load charging, even for a small number of EVs and PHEVs, by utilizing higher efficient intermediate or base- load power plants. For reasons discussed in the Caveats section below, the simplified approach was used because of the complexity of an optimal power plant dispatch analysis that provides sufficient detailed data on the energy requirements and emissions between different charging scenarios. F.3.2 Estimation of Benefits for Fuel Substitution in Vehicular Transportation The challenge for the net benefit estimation strongly depends on the definition of the conventional gasoline technology against which the EV is compared. The literature has discussed this quite extensively, with several suggestions for defining the base-case vehicle: • the fuel economy of today's on-the-road fleet of light-duty vehicles (LDVs), which currently is about 20 mpg (EIA 2008a), reasoning that the new EV purchased in the near term would, on average, replace an existing vehicle represented by the average fuel economy • the corporate average fuel economy standard vehicle, which per EISA 2007 was increased to 35 mpg in 2020 (Public Law 110-140). The argument was put forth that this figure would best represent the competition of a comparable new vehicle to be purchased by 2020 or perhaps before that time. • a vehicle that represents a highly fuel-efficient configuration, such as a gasoline-hybrid electric mid- sized vehicle with a fuel economy of 43 mpg or a turbo-charged direct-injection diesel mid-size car with an fuel efficiency of about 40 mpg (Wang 2001). These figures were argued to represent most realistically the competition of EVs and, thus, should be taken as the conventional vehicle against which to compare the impacts of EVs. At this point, it will not be suggested which of the three base cases is the most appropriate to use for this analysis, as it may depend on the particular policy questions to be considered. However, it should be noted that the higher the fuel economy of the conventional vehicle the higher the bar for EVs to achieve energy and emissions benefits. F.3.3 Benefit Assessment Approach The approach used for this effort is analogous to the methodology described in Kintner-Meyer et al. (2007). It is based on a valley-filling approach that estimates the idle generation capability of the existing grid to support an emerging PHEV customer segment that could be utilized for charging the PHEV/EV batteries. It is the generation that is available after all the existing non-transportation load has been F.5PDF Image | The Smart Grid: An Estimation of the Energy and CO2 Benefits
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