  This paper studies charging scheduling problem of electric vehicles (EVs) in
the scale of a microgrid (e.g., a university or town) where a set of charging
stations are controlled by a central aggregator. A bi-objective optimization
problem is formulated to jointly optimize total charging cost and user
convenience. Then, a close-to-optimal online scheduling algorithm is proposed
as solution. The algorithm achieves optimal charging cost and is near optimal
in terms of user convenience. Moreover, the proposed method applies an
efficient load forecasting technique to obtain future load information. The
algorithm is assessed through simulation and compared to the previous studies.
The results reveal that our method not only improves previous alternative
methods in terms of Pareto-optimal solution of the bi-objective optimization
problem, but also provides a close approximation for the load forecasting.
