In　this　study,　an　optimization　programming　based　on　inexact　stochastic　method　and　factorial　design　was　proposed　to　support　management　of　energy　and　environmental　systems　under　uncertain　conditions.　It　could　be　used　for　analyzing　various　policy　scenarios　associated　with　different　levels　of　economic　penalties　when　promised　targets　are　violated.　Moreover,　it　can　obtain　optimal　decisions　of　primary　energy　supply,　electricity,　and　thermal　power　generation,　capacity　expansion,　and　emission　control　scheme.　The　developed　model　has　been　applied　to　a　case　study　within　a　multifacility,　multiperiod,　and　multidemand-level　context　to　demonstrate　the　feasibility　of　the　proposed　methodology.　Factorial　method　has　been　used　for　sensitivity　analysis　to　address　the　interactive　uncertainties　in　modeling　parameters,　as　well　as　providing　a　trade-off　analysis　between　the　economic　objective　and　the　relevant　energy　and　environmental　policies.　The　generated　approach　will　be　able　to　reflect　dynamic　complexities　in　energy　and　environmental　systems　under　social-economic-environmental　requirements.　It　is　helpful　for　adjusting　the　interrelationship　among　conflicting　economic　objectives　and　environmental　benefits　under　multiple　uncertainties,　formulating　allocation　patterns　of　energy　resources　and　services,　and　identifying　the　effectiveness　of　current　regulations.