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Current studies have shown that the rapid increasing of electric vehicles (EVs) may bring in great impact to the power grid, especially to the directly-connected EV charging station. Considering the cost sensitivity of EV owner and the controllability of the charging process, the pricing and charging power management may be the most effectiveness adjusting mechanisms to reduce the negative impact to the EV charging station. Therefore, we consider the combined scheduling of pricing and power management for EVs in the charging station. First, due to the uncertain EV arrivals, charging requirements and distributed renewable power generation, this problem is represented as a Markov decision process. Second, a bilevel optimization framework is designed for the formulated stochastic programming model. The outer optimization is solved by rollout method while the inner optimization is represented as a mixed-integer programming and solved by typical commercial tools. At last, the operation enhancement and operation benefit improvement of this method are demonstrated by comparing the turnover and the detailed power management of different policies.
Huang et al. (2022) studied this question.