Abstract
A population of drivers was simulated using a microsimulation model. Consistent with the 2001 National Household Travel Survey (NHTS), a wide range of daily driving distance was observed. This heterogeneity implies that some drivers will realize greater fuel savings from driving a plug-in hybrid electric vehicle (PHEV) than others, therefore, consumers who choose to purchase PHEVs may tend to be those who drive farther than average. The model was used to examine the effects of this difference in driving by estimating fuel use, electricity demand and GHG emissions by two populations, one assigned PHEVs at random to some fraction of drivers, and the other assigned PHEVs to drivers who realized operating cost savings at least as great as the amortized incremental cost of the PHEV relative to a comparable conventional vehicle. These two populations showed different distributions of daily driving distance, with the population of PHEV drivers selected on the basis of operating cost savings driving 40% farther per day on average than average drivers. This difference indicates the possible range of driving patterns of future PHEV drivers, which should be taken into account when estimating fuel savings and GHG reductions from PHEVs. For example, if 20% of U.S. vehicles were PHEVs, we find a potential reduction of fuel use of 0.17 gal per day per vehicle if PHEVs substitute randomly for conventional vehicles, whereas the fuel savings is as large as 0.26 gal per day per vehicle if PHEVs are substituted according to operating cost savings. Similar differences in GHG emissions were estimated as well. The effects of electricity demand management on charging PHEVs was examined for these two populations. It was found for both that only a small fraction of PHEVs were impacted by interruptible electricity service (no charging permitted during peak hours). Most PHEV drivers were able to charge sufficiently during off-peak hours and saw little change in operating costs. This implies that interruptible electricity service may impact operating costs of only a small fraction of PHEV drivers.
Highlights
Plug-in hybrid electric vehicles (PHEVs) offer a means to reduce vehicular GHG emissions and petroleum use, but estimation of these reductions is made difficult by uncertainties and heterogeneity in behavior of driver populations
Interruptible electricity service for plug-in hybrid electric vehicle (PHEV) charging was simulated in which no PHEV charging was permitted, either between noon to 10:00 pm or between 8:00 am to 10:00 pm
All PHEVs were assumed to be subject to interruption, and long interruption periods were chosen to represent severe cases of electric demand-side management in order to assess the maximum potential impact on PHEV drivers such interruption might have
Summary
Plug-in hybrid electric vehicles (PHEVs) offer a means to reduce vehicular GHG emissions and petroleum use, but estimation of these reductions is made difficult by uncertainties and heterogeneity in behavior of driver populations. Vyas et al [1] and Samaras and Meisterling [2] estimated the utility factor from the trip distance distribution reported in the 2001 National Household Travel Survey (2001 NHTS) [4] This requires assumptions about how many times per day and where vehicles are charged. These are estimated under different conditions such as with and without interruptible electricity and using different methods to assign PHEVs to drivers From these results, we can gauge the sensitivity of estimated fuel and GHG reduction on assumptions about future PHEV driving patterns and potential impacts of interruptible electricity service on economical operation of PHEVs. Aggregate energy demand and emissions were estimated for a fleet of 7.3 million vehicles, representing the fleet of light-duty passenger vehicles in the state of Michigan. The approach used here requires fewer assumptions and less data, but allows estimation of bounds on energy use and emissions and an assessment of the sensitivity of these to driving patterns
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