Optimal Scheduling Strategy for High Proportion of Electric Vehicles and Wind Turbine Participation

In order to fully tap the flexible interactive resources in the regional energy network and improve the operation economy of the system, the unit combination optimization strategy of considering high proportion of electric vehicles ( EVs ) and wind power access is studied. When a high proportion of EVs are connected to the power grid, the conventional quantitative model is difficult to solve the problem of low computational efficiency caused by large-scale decision variables. A bottom-up method is proposed to describe the flexibility of cluster EVs. Firstly, the physical characteristics of EV battery are analyzed, and the feasible region model of unit EV power is established by depicting the boundary of power and electric energy. Then, a storage battery model is established to characterize the power feasible region of the cluster EV. Finally, the proposed model is applied to the unit commitment problem, and the example results verify its effectiveness. It shows that the optimization strategy of wind/vehicle collaborative participation in unit commitment considering the scheduling flexibility of EV can effectively promote wind power consumption and reduce system operating costs.