The　optimal　capacity　of　energy　storage　facilities　is　a　cornerstone　for　the　investment　and　low-carbon　operation　of　integrated　energy　systems　(IESs).　However,　the　intermittence　of　renewable　energy　and　the　different　operating　characteristics　of　facilities　present　challenges　to　IES　configuration.　Therefore,　a　two-stage　decision-making　framework　is　developed　to　optimize　the　capacity　of　facilities　for　six　schemes　comprised　of　battery　energy　storage　systems　and　hydrogen　energy　storage　systems.　The　objectives　considered　are　to　minimize　the　levelized　cost　of　electricity　(LCOE),　power　abandonment　rate　(PAR)　and　maximize　self-sufficiency　rate　(SSR)　simultaneously.　In　the　first　stage,　each　scheme　is　solved　using　NSGA-II.　In　the　second　stage,　the　weights　of　objective　function　are　determined　by　entropy　weight　method,　while　the　optimal　individual　is　selected　from　the　Pareto　solutions　by　the　technique　for　order　preference　by　similarity　to　ideal　solution　approach.　Life　models　of　battery,　fuel　cell,　and　electrolyzer　are　introduced　to　quantify　device　replacement　costs.　Meanwhile,　carbon　trading　mechanisms　and　time-of-use　tariffs　are　considered　to　assess　environmental　and　economic　benefits.　The　results　show　that　the　hydrogen-electric　coupling　scheme　demonstrated　superior　performance,　with　LCOE,　SSR,　and　PAR　of　0.6416　&　YEN;/kWh,　48.9　%,　and　1.96　%,　respectively,　and　the　hydrogen　storage　tank　is　closely　related　to　LCOE　and　PAR.