The stochastic and timing characteristics of distributed wind generation output, load power and electric vehicles charging load have brought more uncertainties to the optimal allocation of distributed wind generation. Therefore, season-scenario and period-division method is adopted and the stochastic characteristic of plug-in electric vehicles is modeled. Taking annul comprehensive cost as objective function, a distributed wind generation planning model based on timing characteristics is presented using chance constrained programming method. A Monte Carlo simulation embedded genetic algorithm with elite strategy is adopted to solve a typical case and results verify the effectiveness of the proposed model.