  With the rapid growth of electric vehicles (EVs), EV aggregators have been
playing a increasingly vital role in power systems by not merely providing
charging management but also participating in wholesale electricity markets.
This work studies the optimal real-time bidding strategy for an EV aggregator.
Since the charging process of EVs is time-coupled, it is necessary for EV
aggregators to consider future operational conditions (e.g., future EV
arrivals) when deciding the current bidding strategy. However, accurately
forecasting future operational conditions is challenging under the inherent
uncertainties. Hence, there demands a real-time bidding strategy based solely
on the up-to-date information, which is the main goal of this work. We start by
developing an online optimal EV charging management algorithm for the EV
aggregator via Lyapunov optimization. Based on this, an optimal real-time
bidding strategy (bidding cost curve and bounds) for the aggregator is derived.
Then, an efficient yet practical algorithm is proposed to obtain the bidding
strategy. It shows that with the proposed bidding strategy, the aggregator's
profit is nearly offline optimal. Moreover, the wholesale electricity market
clearing result aligns with the individual aggregator's optimal charging
strategy given the prices. Case studies against several benchmarks are
conducted to evaluate the performance of the proposed method.
