A Stochastic Game Approach for PEV Charging Station Operation in Smart Grid

作者：Liu Yuan; Deng Ruilong; Liang Hao^*

来源：IEEE Transactions on Industrial Informatics, 2018, 14(3): 969-979.

DOI：10.1109/TII.2017.2781226

• Charging station
• Nash equilibrium
• plugin electric vehicle (PEV)
• real time pricing (RTP)
• smart grid
• stochastic game (SG)

In the future, smart grid charging stations will be critical infrastructures for plug-in electric vehicle (PEV) to replenish their batteries in a convenient way. Due to the ever-increasing penetration rate of PEVs, how to efficiently manage the loads of PEV charging stations to ensure system efficiency and reliability is amajor challenge faced by the distribution service providers (DSPs) in the smart grid. This challenge is further complicated by the highly dynamic PEV mobility, which results in random PEV arrivals, departures, and charging demands. In order to address this challenge, a stochastic game approach is proposed in this paper to characterize the interactions among DSP, charging stations, and PEV owners, where the randomness in charging decision making processes of PEV owners is modeled by a Markov decision process. Based on the Nash equilibrium solution of the stochastic game, a real time pricing scheme is proposed for the DSP to minimize power distribution losses while ensuring system reliability. The performance of the proposed approach is evaluated via extensive simulations based on the IEEE 123 bus test feeder with real vehicle mobility data fromthe 2009 National Household Travel Survey and the 2010 National Travel Survey.

• 出版日期2018-3