Plug-In Electric Vehicles

Did you know?Using electricity to power an automotive vehicle would cost the equivalent of paying less than $2.00 per gallon of gasoline at current electric prices. In some states, the cost would be under$1.00 per gallon.A typical mid-size sedan, when running on electricity from the current U.S. grid, would have the same carbon footprint as a car that gets 50 miles per gallon (mpg) of gasoline. As more electricity comes from renewable sources, net carbon emissions would be reduced further. Plug-in electric vehicles could be on the market very soon

Factors Affecting Demand for Plug-in Charging Infrastructure: An Analysis of Plug-in Electric Vehicle Commuters

The public sector and the private sector, which includes automakers and charging network companies, are increasingly investing in building charging infrastructure to encourage the adoption and use of plug-in electric vehicles (PEVs) and to ensure that current facilities are not congested. However, building infrastructure is costly and, as with road congestion, when there is significant uptake of PEVs, we may not be able to “build out of congestion.” We modelled the choice of charging location that more than 3000 PEV drivers make when given the options of home, work, and public locations. Our study focused on understanding the importance of factors driving demand such as: the cost of charging, driver characteristics, access to charging infrastructure, and vehicle characteristics. We found that differences in the cost of charging play an important role in the demand for charging location. PEV drivers tend to substitute workplace charging for home charging when they pay a higher electricity rate at home, more so when the former is free. Additionally, socio-demographic factors like dwelling type and gender, as well as vehicle technology factors like electric range, influence the choice of charging location

A New Manhattan Project for Clean Energy Independence

Seven “grand challenges” for the next five years: plug-in electric cars and trucks, carbon capture, solar power, nuclear waste, advanced biofuels, green buildings, and fusionalternative energy, plug-in electric cars, carbon capture, solar power, nuclear waste, viofuels, green, fusion, Oak Ridge

Functional delta-method for the bootstrap of quasi-Hadamard differentiable functionals

The functional delta-method provides a convenient tool for deriving the asymptotic distribution of a plug-in estimator of a statistical functional from the asymptotic distribution of the respective empirical process. Moreover, it provides a tool to derive bootstrap consistency for plug-in estimators from bootstrap consistency of empirical processes. It has recently been shown that the range of applications of the functional delta-method for the asymptotic distribution can be considerably enlarged by employing the notion of quasi-Hadamard differentiability. Here we show in a general setting that this enlargement carries over to the bootstrap. That is, for quasi-Hadamard differentiable functionals bootstrap consistency of the plug-in estimator follows from bootstrap consistency of the respective empirical process. This enlargement often requires convergence in distribution of the bootstrapped empirical process w.r.t.\ a nonuniform sup-norm. The latter is not problematic as will be illustrated by means of examples