The　growing　deployment　of　Internet　services　in　cloud　data　centers　significantly　increases　the　grid　energy　cost　of　cloud　providers.　Considering　the　environmental　effect,　many　of　current　cloud　providers　migrate　to　green　cloud　data　centers　(GCDCs),　and　seek　to　reduce　the　usage　of　brown　energy　by　partially　(or　entirely)　adopting　renewable　energy　sources.　However,　the　temporal　diversity　in　the　grid　price,　wind　speed　and　solar　irradiance　makes　it　a　big　challenge　to　minimize　the　grid　energy　cost　of　a　GCDC　while　meeting　the　performance　of　each　delay　bounded　request.　This　work　proposes　a　Temporal　Request　Scheduling　algorithm　(TRS)　that　jointly　considers　the　temporal　diversity.　TRS　considers　the　long　tail　in　real-life　requests＇　delay,　and　can　provide　strict　delay　assurance　to　all　arriving　requests　by　scheduling　them　to　execute　within　their　delay　bound.　Besides,　this　work　explicitly　provides　mathematical　modeling　of　the　relation　between　the　service　rate　in　a　GCDC　and　the　refusal　of　delay　bounded　requests.　Specifically,　TRS　solves＇　a　constrained　nonlinear　optimization　problem　by　a　hybrid　meta-heuristic　in　each　of　its　iterations.　Compared　with　some　existing　scheduling　methods,　TRS　can　achieve　higher　throughput　and　lower　grid　energy　cost　for　a　GCDC　while　meeting　each　request＇s　delay　requirement.　(C)　2016　Elsevier　Inc.　All　rights　reserved.