Virtual power plant (VPP) is an important means of managing distributed energy. Reasonably formulating pricing strategies for VPP operators and electric vehicle (EV) users can guide EVs to fully consume renewable energy such as wind and solar, thus achieving a win-win situation for VPP operators and EV users. A stackelberg game model is firstly proposed in which a VPP with EVs is used as the electricity sales operator to participate in the orderly charging management of EVs. Operators formulate reasonable electricity selling prices through stackelberg game to guide the orderly charging of EVs, and coordinate various distributed resources to participate in the electricity market. Then, taking into account the volatility of wind power output and the uncertainty of conventional loads, the conditional value at risk (CVaR) theory is introduced into the modeling, and the model is transformed into a mixed integer linear programming problem solved by Karush-Kuhn-Tucker (KKT) conditions and dual theory. Finally, based on an example, the optimal pricing strategy and output plan of VPP operators are given. The influence of different EV proportions, maximum energy storage capacity, and risk preference coefficient on the optimal solution is analyzed, which provides optimization ideas for VPP operators to improve revenue.