With　the　development　of　wind　power　generation,　energy　storage　and　demand　side　management　technology,　the　schedule　of　monthly　electricity　purchase　is　more　uncertain　and　risky.　To　enhance　the　executability　and　economy　of　the　monthly　market　and　reserve　enough　space　to　accommodate　wind　power,　a　bi-level　decision　model,　which　integrates　demand　side　responses,　energy　storage,　wind　power　accommodation　and　day-ahead　electricity　purchase　schedules,　is　proposed　in　this　paper.　In　the　first　layer,　the　monthly　purchase　volume　and　its　hourly　decomposition　schedule　are　optimized.　In　the　second　layer,　factors　of　uncertain　day-ahead　prices　and　economic　risk　are　examined,　and　the　corresponding　dispatching　schedule　of　energy　storage　system　and　thermal　power　in　the　day-ahead　markets　are　further　optimized　to　promote　the　monthly　market　benefit.　The　proposed　methodology　is　illustrated　using　a　realistic　case　study　and　related　affecting　factors　are　analyzed　in　detail.　©　2018