Electric vehicles (EV) have both source and load properties. In order to highlight their positive role in regulating grid load, promoting renewable energy consumption and reducing carbon emissions, this paper constructs an economic dispatching model of electric power system considering carbon trading of EV. Based on the EV charging scenario, the charging mode is subdivided and the quantified analysis method of schedulable capability is proposed. Furthermore, by referring to the carbon emission of traditional fuel vehicles, the carbon quota of EV is analyzed and the carbon trading mechanism of EV is constructed. An optimization model was constructed with the goal of minimizing the total cost of the power generation and carbon emissions of system. The grey wolf optimization(GWO)algorithm is used and the dynamic step evolution strategy and criss-cross strategy are introduced to improve the solving efficiency of economic dispatching model. Example analysis shows that the improved algorithm has higher iteration efficiency and higher solving accuracy. The model can reduce the load peak-valley difference and realize "peak cutting and valley filling". The carbon trading mechanism in the model can guide EV to prioritize the consumption of renewable energy when charging, which improves the consumption rate of renewable energy and reduces the carbon emission cost of the system.