A　data-driven　two-stage　stochastic　optimization　model　for　solving　short-term　hydro-thermal-wind　coordination　scheduling　problem　with　complicated　time-coupled　and　space-related　characteristics　is　proposed　in　this　paper.　The　generation,　emission　and　power　fluctuation　costs　in　the　day-ahead　scheduling　stage　and　power　regulation　costs　by　hydro-thermal　units,　wind　curtailment　and　load　shedding　costs　in　the　real-time　scheduling　stage　is　formulated　as　the　objective　function　of　proposed　model.　Moreover,　a　dynamic　extreme　scenario　generation　and　reduction　method　is　introduced　to　deal　with　wind　power　uncertainty.　The　relationship　between　hydropower　output,　volume,　inflow,　discharge　and　upstream　water　for　the　multi-reservoir　cascaded　hydro　plants　is　converted　into　a　series　of　linear　constraints,　and　the　practical　constraints　of　prohibited　operation　zones　for　thermal　units　are　taken　into　account.　As　a　result,　the　proposed　model　can　be　transformed　into　a　mixed-integer　linear　programming　problem　to　solve.　Finally,　case　studies　are　carried　out　on　the　modified　IEEE　24-bus　system　comprising　of　six　thermal　units,　a　multi-chain　cascade　of　four　hydro　plants　and　one　wind　farm,　and　simulation　results　verify　the　effectiveness　of　the　proposed　coordination　scheduling　model　and　method.　©　2021　Elsevier　Ltd