Wind power, photovoltaic power output uncertainty, carbon emissions price and the price of multiple random factors have brought new problems to the power system of production and operation, through the price mechanism to guide the electric vehicle can promote the peak, but the static tou may produce a new high peak. In view of the above background, this paper proposes a two stage optimization model based on dynamic time-sharing price. The optimization model established before the partition of peak and valley time, to solve the problem with fuzzy C means clustering algorithm; on this basis, the establishment of wind power, photovoltaic, carbon emission permits the joint scheduling model with stochastic price and the method of the alpha hyper number is improved to solve the multiple random factors.The model is applied to a numerical example, and the influence of the relevant factors is analyzed. The result not only proves the rationality of the model, but also provides a reference for the scheduling decision.
