V2G Dynamic Tariff Strategy Based On Multiple Games

The increasing number of electric vehicles (EVs) brings about a huge impact on the safe and stable operation of the power system because of increasing random charging load demands. But a large number of on-board batteries can become an important resource for the ancillary service of power system if proper demand response technology is adopted. In this paper, for the scenario of peak-shaving and valley-filling of power system ancillary service, an electricity price mechanism is proposed to guide the orderly charging and discharging of EVs, aiming at the income balance of the power grid (PG), EV users, and electric vehicle aggregator (EVA). By the proposed method, firstly, an evolutionary game model is proposed to obtain the charge and discharge price range of EVs. Secondly, using the price range above and the cooperative game theory, the dynamic charging and discharging electricity price of EVs (here named as V2G price) are determined with equal distribution of the interests among the three parties. Finally, taking 10,000 EVs participating in peak-shaving and valley-filling as an example, the economy of dispatching EVs by the proposed method is compared with that by the traditional time-of-use electricity price model. The simulation results show that the V2G electricity price strategy proposed in this paper can reduce the peak-to-valley difference of the PG and keep the income of the PG, EV and EVA more balanced.