  The large-scale integration of plug-in electric vehicles (PEVs) to the power
grid spurs the need for efficient charging coordination mechanisms. It can be
shown that the optimal charging schedule smooths out the energy consumption
over time so as to minimize the total energy cost. In practice, however, it is
hard to smooth out the energy consumption perfectly, because the future PEV
charging demand is unknown at the moment when the charging rate of an existing
PEV needs to be determined. In this paper, we propose an Online cooRdinated
CHARging Decision (ORCHARD) algorithm, which minimizes the energy cost without
knowing the future information. Through rigorous proof, we show that ORCHARD is
strictly feasible in the sense that it guarantees to fulfill all charging
demands before due time. Meanwhile, it achieves the best known competitive
ratio of 2.39. To further reduce the computational complexity of the algorithm,
we propose a novel reduced-complexity algorithm to replace the standard convex
optimization techniques used in ORCHARD. Through extensive simulations, we show
that the average performance gap between ORCHARD and the offline optimal
solution, which utilizes the complete future information, is as small as 14%.
By setting a proper speeding factor, the average performance gap can be further
reduced to less than 6%.
