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.　©　2018　Elsevier　Ltd