The　multi-energy　microgrid　(MEMG)　plays　a　significant　role　in　improving　energy　utilization　and　flexibility　of　energy　supply.　However,　the　uncertainties　of　wind　turbine　(WT)　and　load　demand　in　MEMG　are　inevitable,　which　brings　challenges　to　MEMG　scheduling.　To　deal　with　the　uncertainties　of　MEMG　with　minimum　operational　cost,　this　paper　proposes　a　tube　model　predictive　control　(TMPC)-based　optimal　scheduling　strategy　for　MEMG　coupled　with　electricity,　heat,　and　natural　gas.　The　proposed　TMPC　consists　of　two　MPCs,　namely　the　nominal　MPC　and　the　ancillary　MPC.　Firstly,　without　considering　the　uncertainties,　the　nominal　MPC　generates　reference　trajectories　with　the　goal　of　economy　on　tightened　constraints.　Further,　considering　the　multiple　uncertainties,　the　ancillary　MPC　makes　scheduling　decisions　for　the　actual　system　via　steering　the　ancillary　trajectories　to　those　provided　by　the　nominal　MPC.　In　this　way,　the　proposed　TMPC-based　strategy　has　robustness　against　uncertainties　of　MEMG.　Simulations　on　a　grid-connected　MEMG　are　carried　out　to　show　the　effectiveness　and　the　computational　efficiency　of　the　proposed　TMPC-based　optimal　scheduling　strategy.　©　2022　IEEE.