  As an essential measure to combat global warming, electric vehicles (EVs)
have witnessed rapid growth. Flexible EVs can enhance power systems' ability to
handle renewable generation uncertainties. How EV flexibility can be utilized
in power grid operation has captured great attention. However, the direct
control of individual EVs is challenging due to their small capacity and large
number. Hence, it is the aggregator that interacts with the grid on behalf of
the EVs by characterizing their aggregate flexibility. In this paper, we focus
on the aggregate EV power flexibility characterization problem. First, an
offline model is built to obtain the lower and upper bounds of the aggregate EV
power flexibility region. It ensures that any trajectory within the region is
feasible. Then, considering that parameters such as real-time electricity
prices and EV arrival/departure times are not known in advance, an online
algorithm is developed based on Lyapunov optimization techniques. We provide a
theoretical bound for the maximum charging delay under the proposed online
algorithm. Furthermore, real-time feedback is designed and integrated into the
proposed online algorithm to better unlock EV power flexibility. Comprehensive
performance comparisons are carried out to demonstrate the advantages of the
proposed method.
