Since the intermittency and volatility of wind power has restricted its penetration into power grid, coordination scheduling of flexible resources and wind energy becomes a promising technique for promoting wind power utilization. Hence, this paper integrates large-scale electric vehicles (EVs) with wind power generation to formulate multi-objective hydro-thermal-wind with EVs scheduling (MOHTWES) problem. And what's more, an improved multi-objective particle swarm optimization (IMOPSO) algorithm is proposed for solving the above problem with various constraints. By introducing a unique dual population evolution mechanism and a hierarchical elitism preserving strategy based on crowding entropy, IMOPSO can achieve excellent and well-distributed Pareto optimal solutions in objective space. Furthermore, a set of constraint handling strategies are utilized to guarantee that the solutions obtained are in feasible region. Finally, a daily scheduling problem of hydro-thermal system is used to verify the performance of IMOPSO, the numerical results of which shows the Pareto optimal solutions obtained by IMOPSO have greater advantages than the comparison algorithms. Furthermore, it can be concluded from the simulation results for MOHTWES problem that, smart scheduling of EVs integrated with wind energy can promote wind power utilization and reduce the generation cost and emission simultaneously. (C) 2018 Elsevier Ltd. All rights reserved.