The　traditional　robust　optimization　and　stochastic　optimization　methods　result　in　some　limitations　and　shortcomings　in　dealing　with　the　uncertainty　problem　of　the　renewable　energy　generation,　such　as　wind　power　generation.　Based　on　distributionally　robust　optimization,　this　paper　focuses　on　the　day-ahead　economical　dispatch　problem　of　electricity-gas-heat　integrated　energy　system　(EGH-IES)　considering　the　uncertainty　of　wind　power.　The　Kullback-Leibler　(KL)　divergence　is　taken　as　a　measure　of　the　distance　between　a　distribution　function　and　the　nominal　distribution,　and　an　ambiguity　set　of　distribution　function　of　wind　power　is　constructed.　Then,　taking　the　total　operating　cost　of　the　system　as　the　objective　function,　a　robust　chance　constrained　optimization　model　for　day-ahead　economic　dispatch　of　EGH-IES　is　established.　Moreover,　this　model　is　transformed　into　a　deterministic　mixed　integer　linear　optimization　model　which　can　be　solved　by　commercial　solvers.　Finally,　case　studies　demonstrate　the　effectiveness　of　the　proposed　method,　and　the　effects　of　technology　of　power　converted　into　gas　and　transmission　delay　of　the　heating　network　on　wind　power　consumption　are　discussed.　©　2020,　Power　System　Technology　Press.　All　right　reserved.