With　the　consideration　of　the　capacity　cost　and　energy　cost　of　system　spinning　reserve,　the　reduced　outage　cost　due　to　the　purchase　of　spinning　reserve　and　the　dispersion　degree　of　spinning　reserve　benefit,　the　risk　bias　coefficient　is　introduced　and　the　weighted　semi-variance　of　security　portfolio　is　adopted　to　measure　the　risk.　A　spinning　reserve　benefit-risk　model　with　the　maximum　expected　spinning　reserve　benefit　and　minimum　risk　as　its　optimization　objectives　is　built　based　on　the　weighted　semi-variance　for　the　power　system　with　wind　power.　The　Monte　Carlo　method　is　used　to　simulate　the　actual　load-power　deviation　and　wind　power　prediction　error,　and　the　multi-objective　crisscross　optimization　algorithm　is　used　to　obtain　the　effective　frontier　of　expected　spinning　reserve　benefit-risk　and　the　day-ahead　spinning　reserve　plan,　as　well　as　the　influences　of　risk　bias　coefficient,　reliability　level,　prediction　error,　load-loss　price　and　spinning　reserve　price　on　the　expected　spinning　reserve　benefit　and　risk.　The　rationality　of　the　proposed　model　is　verified　by　the　example.　©　2017,　Electric　Power　Automation　Equipment　Press.　All　right　reserved.