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Accurately evaluating the real-time flexibility of electric vehicles (EVs) in a charging station is necessary for EV aggregators to offer ancillary services. However, regulation-caused uncertain state-of-charge and random departure behavior complicate the evaluation and badly impact the evaluation accuracy. To resolve this issue, this letter proposes a distributionally robust real-time flexibility evaluation model that formulates the uncertain departure behavior and state-of-charge of EVs in an online updating pattern. Thanks to dualization, this model can be efficiently solved via off-the-shelf solvers. Case studies validate the superiority of the proposed method and its scalability regarding the charging station capacity.
Li et al. (Mon,) studied this question.