  Electric vehicles (EVs) add significant load on the power grid as they become
widespread. The characteristics of this extra load follow the patterns of
people's driving behaviours. In particular, random parameters such as arrival
time and charging time of the vehicles determine their expected charging demand
profile from the power grid. In this paper, we first present a model for
uncoordinated charging power demand of EVs based on a stochastic process and
accordingly we characterize an EV's expected daily power demand profile. Next,
we illustrate it for different charging time distributions through simulations.
This gives us useful insights into the long-term planning for upgrading power
systems' infrastructure to accommodate EVs. Then, we incorporate departure time
as another random variable into this modelling and introduce an autonomous
demand response (DR) technique to manage the EVs' charging demand. Our results
show that, it is possible to accommodate a large number of EVs and achieve the
same peak-to-average ratio (PAR) in daily aggregated power consumption of the
grid as when there is no EV in the system. This peak value can be decreased
further significantly when we add vehicle-to-grid (V2G) capability in the
system.
