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Intelligent Charging Management of Electric Vehicles Considering Dynamic User Behavior and Renewable Energy A Stochastic Game Approach

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Document pages: 11 pages

Abstract: Uncoordinated charging of a rapidly growing number of electric vehicles (EVs)and the uncertainty associated with renewable energy resources may constitute acritical issue for the electric mobility (E-Mobility) in the transportationsystem especially during peak hours. To overcome this dire scenario, weintroduce a stochastic game to study the complex interactions between the powergrid and charging stations. In this context, existing studies have not takeninto account the dynamics of customers preference on charging parameters. Inreality, however, the choice of the charging parameters may vary over time, asthe customers may change their charging preferences. We model this behavior ofcustomers with another stochastic game. Moreover, we define a quality ofservice (QoS) index to reflect how the charging process influences customers choices on charging parameters. We also develop an online algorithm to reachthe Nash equilibria for both stochastic games. Then, we utilize real data fromthe California Independent System Operator (CAISO) to evaluate the performanceof our proposed algorithm. The results reveal that the electricity cost withthe proposed method can result in a saving of about 20 compared to thebenchmark method, while also yielding a higher QoS in terms of charging andwaiting time. Our results can be employed as guidelines for charging serviceproviders to make efficient decisions under uncertainty relative to powergeneration of renewable energy.

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