As　wind　power　penetration　becomes　increasingly　significant,　the　impact　of　the　intermittent　and　stochastic　wind　energy　on　power　systems　reliability　urgently　needs　to　be　assessed.　This　paper　examines　the　impacts　of　different　wind　speed　simulation　methods　on　the　adequacy　evaluation　by　the　conditional　reliability　indices.　First,　the　seasonal　property,　diurnal　distributions,　and　autocorrelation　of　wind　speeds　at　a　particular　site　are　investigated　with　the　practical　observed　wind　speed　data,　and　several　typical　wind　speed　simulation　methods　are　discussed.　Then,　after　analyzing　the　drawbacks　of　the　traditional　unconditional　expected-value-based　reliability　indices,　a　series　of　conditional　reliability　indices　are　proposed,　making　it　possible　to　incorporate　risk　preference　into　the　reliability　assessment.　Furthermore,　an　adequacy　evaluation　process　based　on　sequential　Monte　Carlo　approach　is　established.　Finally,　three　wind　power　integration　scenarios　are　designed　in　the　modified　IEEE-RTS,　and　the　impacts　of　different　wind　speed　simulation　methods　on　the　conditional　reliability　indices　in　the　three　scenarios　are　thoroughly　compared.　Numerical　results　have　shown　that　time　series　methods　agree　well　with　the　observed　wind　speed　method　in　the　conditional　reliability　indices;　the　conditional　reliability　indices　in　the　probability　sampling　method　present　the　property　of　high　frequency　and　short　duration,　especially　in　the　high　damage　domain;　the　mean　observed　wind　speed　method　leads　to　relatively　optimistic　results,　with　higher　conditional　probability　of　the　healthy　state　and　lower　conditional　probabilities　of　the　marginal　and　at-risk　states;　and　the　healthy　state　in　this　method　is　of　lower　occurrence　frequency　and　longer　duration.　Copyright　(c)　2013　John　Wiley　&　Sons,　Ltd.