To　solve　the　problem　of　a　mismatch　between　the　available　renewable　energy　and　the　demand　for　load　that　is　caused　by　access　to　a　high　ratio　of　renewable　energy,　this　paper　proposes　a　method　to　optimally　configure　the　system＇s　capacity　for　a　hybrid　energy　storage　system　(HESS)　based　on　a　comprehensive　system　of　indices　for　cluster　division.　We　first　design　a　clustering　algorithm　by　combining　the　improved　self-adaptive　density　peak　clustering　(ISDPC)　algorithm　with　the　K-means　clustering　algorithm　to　classify　the　output　curves　of　renewable　energy　and　generate　typical　scenarios.　We　then　propose　the　system　indices　for　cluster　division　that　is　composed　of　modularity,　active　balance　of　power,　and　net　fluctuations　in　load.　This　system　is　used　for　cluster　division　of　distribution　network.　The　net　load　in　the　cluster　is　then　decomposed　into　high　frequency　components　and　low　frequency　components　by　using　variational　mode　decomposition　to　obtain　reference　values　of　power　for　power-based　and　energy-based　storage.　Finally,　we　establish　an　optimal　model　to　configure　the　capacity　of　the　HESS　with　the　objective　of　minimizing　the　annual　cost　of　its　configuration　and　net　fluctuations　in　load,　and　use　the　non-dominated　sorting　genetic　algorithm-II　(NSGA-II)　algorithm　to　solve　it.　Simulations　of　the　modified　IEEE　33-bus　distribution　system　were　used　to　verify　the　effectiveness　and　feasibility　of　the　proposed　method.　©　2023　IEEE.