Distributed　energy　systems　are　considered　as　a　promising　technology　for　sustainable　development　and　have　become　a　popular　research　topic　in　the　areas　of　building　energy　systems.　This　work　presents　a　case　study　of　optimizing　an　integrated　distributed　energy　system　consisting　of　combined　heat　and　power　(CHP),　photovoltaics　(PV),　and　electric　and/or　thermal　energy　storage　for　a　hospital　and　large　hotel　buildings　located　in　Texas　and　California.　First,　simulation　models　for　all　subsystems,　which　are　developed　individually,　are　integrated　together　according　to　a　control　strategy　designed　to　satisfy　both　the　electric　and　thermal　energy　requirements　of　a　building.　Subsequently,　a　multi-objective　particle　swarm　optimization　(MOPSO)　is　employed　to　obtain　an　optimal　design　of　each　subsystem.　The　objectives　of　the　optimization　are　to　minimize　the　simple　payback　period　(PBP)　and　maximize　the　reduction　of　carbon　dioxide　emissions　(RCDE).　Finally,　the　energy　performance　for　the　selected　building　types　and　locations　are　analyzed　after　the　optimization.　Results　indicate　that　the　proposed　optimization　method　could　be　applied　to　determine　an　optimal　design　of　distributed　energy　systems,　which　reaches　a　trade-off　between　the　economic　and　environmental　performance　for　different　buildings.　With　the　presented　distributed　energy　system,　a　peak　shaving　in　electricity　of　about　300　kW　and　a　reduction　in　boiler　fuel　consumption　of　610　kW　could　be　attained　for　the　hospital　building　located　in　California　for　a　winter　day.　For　the　summer　and　transition　seasons,　electricity　peak　shaving　of　800　kW　and　600　kW　could　be　achieved,　respectively.