This　study　proposes　a　bi-level　stochastic　framework　to　address　optimal　scheduling　of　energy　hub　(EH)　in　a　pool-based　short-term　market　considering　electrical-thermal-water　demands.　EH　acts　as　an　independent　price-maker　producer　in　a　day-ahead　electricity　market　aiming　to　maximise　its　profit.　The　market　settlement　mechanism　is　constructed　as　the　pay-at-market-clearing　price　(MCP),　where　each　producer/consumer　is　paid　at　the　MCP.　The　problem　model　is　formulated　as　a　bi-level　optimisation　approach　in　a　stochastic　environment,　in　which　the　upper　level　defines　the　profit　maximisation　of　the　proposed　strategic　producer,　whereas　the　lower-level　expresses　the　dispatch　cost　of　the　considered　power　grid.　This　results　in　a　problem　formulation　with　mathematical　equilibrium　constraints　which　is　transformed　into　a　new　mixed-integer　linear　programme　based　on　Karush-Kuhn-Tucker　conditions.　A　stochastic　framework　based　on　unscented　transform　is　developed　to　model　the　high　uncertainties　of　EH　water　demand,　EH　thermal　demand,　EH　electric　demand,　generators　and　loads　submitted　price　to　the　market.　The　simulation　results　on　the　IEEE　test　system　advocate　the　effectiveness　and　appropriate　performance　of　the　proposed　strategic　EH　producer　in　the　electricity　market　and　its　effect　on　the　locational　marginal　prices　of　buses　in　a　transmission-constrained　market.