The　random　output　of　renewable　energy　and　the　disorderly　grid　connection　of　electric　vehicles　(EV)　will　pose　challenges　to　the　safe　and　stable　operation　of　the　power　system.　In　order　to　ensure　the　reliability　and　symmetry　of　the　microgrid　operation,　this　paper　proposes　a　microgrid　optimization　scheduling　strategy　considering　the　access　of　EVs.　Firstly,　in　order　to　reduce　the　impact　of　random　access　to　EVs　on　power　system　operation,　a　schedulable　model　of　an　EV　cluster　is　constructed　based　on　the　Minkowski　sum.　Then,　based　on　the　wavelet　neural　network　(WNN),　the　renewable　energy　output　is　predicted　to　reduce　the　influence　of　its　output　fluctuation　on　the　operation　of　the　power　system.　Considering　the　operation　constraints　of　each　unit　in　the　microgrid,　the　network　active　power　loss　and　node　voltage　deviation　are　taken　as　the　optimization　objectives,　and　the　established　microgrid　model　is　equivalently　transformed　via　second-order　cone　relaxation　to　improve　its　solution　efficiency.　Based　on　network　reconfiguration　and　flexible　load　participation　in　demand　response,　the　economy　and　reliability　of　system　operation　are　improved.　Finally,　the　feasibility　and　effectiveness　of　the　proposed　method　are　verified　based　on　the　simulation　examples.