Amid　rising　energy　demands　and　environmental　concerns,　integrated　energy　systems　(IESs)　face　conflicting　interests.　Conventional　strategies　of　interest　distribution　face　issues　such　as　irrational　resource　allocation.　Accordingly,　establishing　energy　trading　strategies　with　multiple　stakeholders　becomes　essential.　This　paper　proposes　a　robust　optimization　(RO)　for　IESs　based　on　multi-energy　trading　to　reduce　energy　trading　cost.　In　this　regard,　a　single-leader-multi-follower　Stackelberg　game　is　first　modeled　where　IES　acts　as　the　leader,　and　the　users　and　the　electric　vehicles　(EVs)　act　as　the　followers.　Secondly,　this　model　is　transformed　into　a　single-layer　linear　model　and　integrated　into　the　multi-stage　RO.　With　this,　the　nonanticipativity　in　the　two-stage　RO　can　be　effectively　handled.　Besides,　by　constructing　multi-interval　uncertainty　sets　for　renewable　energy,　load,　and　electricity　prices,　the　conservatism　of　the　model　is　reduced,　making　the　optimization　results　closer　to　actual　condition.　Noteworthy　that　the　Nash　bargaining　method　ensures　a　fair　distribution　of　benefits　among　IESs　and　encourages　them　to　participate　in　energy　trading.　Finally,　the　multi-energy　trading　model　is　solved　using　the　prediction-correction-based　alternating　direction　method　with　multipliers　(PCB-ADMM)　algorithm.　The　PCB-ADMM　not　only　protects　each　IES＇s　privacy　but　also　has　less　execution　time　than　the　ADMM　algorithm.　The　effectiveness　of　the　proposed　strategy　is　validated　through　simulation　using　Matlab.　©　2024