With　the　continuous　expansion　of　renewable　energy　installation　capacity　and　the　persistent　advancement　of　integrated　energy　system　research,　the　gas-fired　units　deepen　the　integration　of　power　system　and　natural　gas　system　as　the　coupled　components　and　provide　a　new　way　for　renewable　energy　accommodation.　Since　the　stochastic　scheduling　method,　interval　optimization　and　robust　optimization　algorithms　have　their　own　shortcomings　in　dealing　with　wind　power　uncertainty,　a　distributionally　robust　optimization　approach　based　on　fuzzy　set　of　wind　power　prediction　error　is　proposed　to　solve　the　collaborative　dispatch　problem　for　power-gas　coupled　system.　Firstly,　the　principal　component　analysis　is　adopted　to　extract　the　temporal-spatial　scale　correlation　characteristics　of　high-dimensional　prediction　error　vector,　and　a　series　of　moment　functions　are　introduced　to　describe　the　distribution　information　of　prediction　errors　to　construct　the　corresponding　fuzzy　set.　Then,　a　two-stage　distributionally　robust　optimal　ecomomic　dispatch　model　is　established.　The　first　stage　is　used　to　make　the　unit　commitment　decision,　power　output　and　reserve　configuration　by　units,　and　the　second　stage　is　used　to　identify　the　worst-case　distribution　of　wind　power　to　ensure　the　effectiveness　of　the　scheduling　strategy　determined　in　the　first　stage.　Combining　the　linear　decision　rule　and　dual　theory,　the　above　semi-infinite　optimization　problem　can　be　transformed　into　a　finite-dimensional　optimization　problem　and　then　solved.　Finally,　the　simulation　results　verify　the　validity　of　the　proposed　model　and　solution　method.　©　2020　Automation　of　Electric　Power　Systems　Press.