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.　(C)　2021　Elsevier　Ltd.　All　rights　reserved.