  Uncoordinated charging of a rapidly growing number of electric vehicles (EVs)
and the uncertainty associated with renewable energy resources may constitute a
critical issue for the electric mobility (E-Mobility) in the transportation
system especially during peak hours. To overcome this dire scenario, we
introduce a stochastic game to study the complex interactions between the power
grid and charging stations. In this context, existing studies have not taken
into account the dynamics of customers' preference on charging parameters. In
reality, however, the choice of the charging parameters may vary over time, as
the customers may change their charging preferences. We model this behavior of
customers with another stochastic game. Moreover, we define a quality of
service (QoS) index to reflect how the charging process influences customers'
choices on charging parameters. We also develop an online algorithm to reach
the Nash equilibria for both stochastic games. Then, we utilize real data from
the California Independent System Operator (CAISO) to evaluate the performance
of our proposed algorithm. The results reveal that the electricity cost with
the proposed method can result in a saving of about 20% compared to the
benchmark method, while also yielding a higher QoS in terms of charging and
waiting time. Our results can be employed as guidelines for charging service
providers to make efficient decisions under uncertainty relative to power
generation of renewable energy.
