High　penetration　of　wind　power　generation　and　deregulated　electricity　market　brings　a　great　challenge　to　the　electricity　system　operators.　It　is　crucial　to　make　optimal　strategy　among　various　generation　units　and　spinning　reserve　for　supporting　the　system　safety　operation.　By　integrating　interval　two-stage　programming　and　stochastic　robust　programming,　this　paper　proposes　a　novel　robust　model　for　day　ahead　dispatch　and　risk-aversion　management　under　uncertainties.　In　the　proposed　model,　the　uncertainties　are　expressed　as　interval　values　with　different　scenario　probability.　The　proposed　method　requires　low　computation,　and　still　retains　the　complete　information.　A　case　study　is　to　validate　the　effectiveness　of　this　approach.　lacing　the　uncertainties　of　future　demand　and　electricity　price,　the　system　operators　need　to　make　optimal　dispatch　strategy　for　thermal　power　units　and　wind　turbine,　and　arrange　proper　spinning　reserve　and　flexible　demand　response　program　to　mitigate　wind　power　forecasting　error.　The　optimal　strategies　provide　the　system　operators　with　better　trade-off　between　the　maximum　benefits　and　the　minimum　system　risk.　In　additional,　two　different　market　rules　are　compared.　The　results　show　that　extra　financial　penalty　for　the　wind　power　dispatch　deviation　is　another　efficient　way　to　enhance　the　risk　consciousness　of　decision　makers　and　lead　to　more　conservative　strategy.　(C)　2016　Elsevier　Ltd.　All　rights　reserved.