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    Abstract: In order to solve the problems of intermittent wind power output and distribution network power fluctuation caused by a large number of electric vehicles randomly accessing to the distribution network to charge and discharge, the paper proposes a collaborative optimal scheduling strategy of electric vehicles and wind power based on dynamic time-of-use price. First, models of power battery loss and wind power output are established to improve the needs of both users and power grids. Second, with the consideration of power grid stability and costs and benefits of electric vehicle users’ charging and discharging in different periods, a mathematical model is built to realize the goal of minimizing the user charging costs,the comprehensive load fluctuation of the distribution network and the network loss costs. Third, to optimize the multivariable and multi-objective constraints, the maximum fuzzy satisfaction method is adopted to normalize the multi-objective problem; then, the improved sine cosine optimization algorithm is adopted to optimize the charging and discharging power and price which are used as variables. According to the multi-scenario simulation results of IEEE 33 node example, this strategy is able to dynamically adjust the electricity price with the change of electric vehicle network access, enhance the wind power consumption, and have better effects on reducing peak valley difference, charging cost and network loss.

    Key words: electric vehicles; wind power collaborative optimal scheduling; dynamic price; sine cosine optimization algorithm