In　the　context　of　building　a　new　type　of　power　system,　the　optimal　operation　of　high-proportion　new-energy　distribution　networks　(HNEDNs)　is　a　current　hot　topic.　In　this　paper,　a　stochastic　distribution　robust　optimization　method　for　HNEDNs　that　considers　energy-storage　refinement　modeling　is　proposed.　First,　an　energy-storage　lifetime　loss　model　based　on　the　rainfall-counting　method　is　constructed,　and　then　an　optimal　operation　model　of　an　HNEDN　considering　energy　storage　refinement　modeling　is　constructed,　aiming　to　minimize　the　total　operation　cost　while　taking　into　account　the　energy　cost　and　the　penalty　cost　of　abandoning　wind　and　solar　power.　Then,　a　source-load　uncertainty　model　of　HNEDN　is　constructed　based　on　the　Wasserstein　distance　and　conditional　value　at　risk　(CvaR)　theory,　and　the　HNEDN　optimization　model　is　reconstructed　based　on　the　stochastic　distribution　robust　optimization　method;　based　on　this,　the　multiple　linearization　technique　is　introduced　to　approximate　the　reconstructed　model,　which　aims　to　both　reduce　the　difficulty　in　solving　the　model　and　ensure　the　quality　of　the　solution.　Finally,　the　modified　IEEE　33-bus　power　distribution　system　is　used　as　an　example　for　case　analysis,　and　the　simulation　results　show　that　the　method　presented　in　this　paper,　through　reducing　the　loss　of　life　in　the　battery　storage　device,　can　reduce　the　average　daily　energy　storage　depreciation　cost　compared　to　an　HNEDN　optimization　method　that　does　not　take　the　energy　storage　life　loss　into　account;　this,　in　turn,　reduces　the　total　operating　cost　of　the　system.　In　addition,　the　stochastic　distribution　robust　optimization　method　used　in　this　paper　can　adaptively　adjust　the　economy　and　robustness　of　the　HNEDN　operation　strategy　according　to　the　confidence　level　and　the　available　historical　sample　data　on　new　energy-output　prediction　errors　to　obtain　the　optimal　HNEDN　operation　strategy　when　compared　with　other　uncertainty　treatment　methods.