Multiple　uncertainties　caused　by　renewable　energy　and　loads　bring　challenges　to　the　secure　operation　of　integrated　energy　system　(IES).　Concurrently,　the　centralized　control　methods　based　on　global　information　of　IES　cannot　preserve　the　data　privacy　of　each　individual　subsystem.　To　deal　with　these　issues,　this　paper　proposes　a　distributed　two-stage　robust　optimization　(TRO)　scheduling　strategy　for　IES　considering　gas　inertia　and　biogas–wind　renewables.　To　address　the　uncertainties　of　wind　turbines　output　and　electricity　loads　in　IES,　a　TRO　model　is　first　established,　and　the　column　and　constraint　generation　(C&CG)　algorithm　is　employed　to　handle　the　min–max–min　problem　of　TRO　model.　On　this　basis,　a　distributed　cooperative　scheduling　framework　based　on　the　consensus-based　alternating　direction　method　of　multipliers　(C-ADMM)　for　IES　is　developed,　which　requires　no　overall　system　information　but　only　local　information.　Additionally,　natural　gas　pipelines　that　consider　gas　inertia　are　used　as　gas　storage　facilities,　which　provides　IES　with　additional　scheduling　resources　and　flexibility.　Furthermore,　an　adaptive　step-size　strategy　is　proposed　to　adjust　the　step-size　of　ADMM　in　real　time,　which　reduces　the　dependence　of　ADMM　performance　on　the　initial　parameters　selection　and　improves　its　convergence　performance.　The　simulation　results　in　a　three-subsystem　joint　IES　are　presented　to　demonstrate　the　effectiveness　of　the　proposed　distributed　TRO　scheduling　strategy.　©　2023　Elsevier　Ltd