In　order　to　adapt　to　active　distribution　network　which　will　have　large-scale　distributed　generation　(DG)　and　high　level　of　automation　in　the　future,　active　management　measures　must　be　considered　in　the　planning　stage　to　optimize　system　operation.　And　the　existing　research　of　distribution　network　reactive　compensation　planning　ignores　the　uncertainty　of　DG　and　load.　Aiming　to　solve　the　problems,　this　paper　proposes　reactive　compensation　optimal　allocation　model　in　active　distribution　network　based　on　the　uncertainties　of　intermittent　DG　and　load　power.　The　lowest　reactive　compensation　capacitors　investment　cost　and　network　loss　cost　are　taken　as　the　objective　of　upper　level.　And　considering　two　active　management　measures　including　regulating　reactive　power　compensation　capacity　and　regulating　the　on-load　tap　changer,　the　lower　level　optimizes　for　each　scene.　This　paper　uses　K-　means　clustering　method　to　reduce　the　scene,　and　combines　with　the　harmonic　search　algorithm　and　particle　swarm　algorithm　to　solve　the　model.　And　simulative　results　of　IEEE-33　distribution　system　verify　the　effectiveness　of　the　model　and　solution　methods.　©　2017,　Power　System　Protection　and　Control　Press.　All　right　reserved.