Connecting　electric　vehicles　(EV)　to　the　renewable　energy　microgrid　is　conducive　to　reduce　environmental　pollution　and　improve　energy　structure.　However,　the　random　volatility　of　EV　charging　load　may　increase　the　difficulty　of　economic　dispatch　of　the　microgrid.　In　order　to　achieve　a　cost　effective　and　reliable　hybrid　generation　system,　an　optimal　scheduling　method　of　microgrids　with　electric　vehicles　based　on　an　improved　salp　swarm　algorithm　(ISSA)　is　studied.　As　the　traditional　salp　swarm　algorithm　(SSA)　algorithm　has　the　disadvantages　of　premature　convergence　and　getting　stuck　in　local　optimum,　the　proposed　ISSA　algorithm　used　Tent　chaos　map　to　generate　the　initial　population,　which　can　increase　the　diversity　of　the　population.　Then,　a　dynamic　control　parameter　is　added　to　maintain　a　better　balance　between　global　search　and　local　search　of　the　algorithm.　At　the　same　time,　orthogonal　centroid-opposition　based　learning　strategy　(OCOBL)　is　introduced　to　update　the　position　information　of　each　salp.　This　scheme　can　increase　the　global　search　ability　and　prevent　the　algorithm　from　falling　into　local　optimum.　Finally,　the　ISSA　algorithm　is　applied　for　optimal　dispatch　of　the　microgrid　with　electric　vehicles　in　the　grid-connected　and　islanded　modes,　and　the　simulation　confirm　the　efficacy　of　the　ISSA　technique　compared　with　other　meta-heuristic　algorithms.　The　results　also　show　that　the　operating　cost　in　two　operation　models　are　respectively　reduced　up　to　29.1%　and　20.0%　under　the　proposed　algorithm,　which　demonstrates　the　effectiveness　and　applicability　of　the　proposed　method.　©　2025　South　China　University　of　Technology.　All　rights　reserved.