Hydrogen　is　a　promising　energy　source　and　hydrogen　refueling　stations　(HRS)　are　the　main　hydrogen　supply　infrastructures.　Unwanted　hydrogen　leaks　and　releases　at　the　hydrogen　station　may　cause　serious　explosion　accidents　and　even　induce　domino　effects　due　to　intensive　hazardous　equipment　in　the　station.　However,　scant　attention　has　been　accorded　to　the　dynamic　risks　of　fire,　explosion,　and　domino　effects　at　HRS,　posing　a　threat　to　the　safe　functioning　of　HRS　and　the　advancement　of　the　hydrogen　energy.　This　study　thus　first　develops　Dynamic　Bayesian　networks　to　model　the　primary　fire　and　explosion　accidents　as　well　as　domino　effects　at　HRS.　By　the　developed　models,　the　critical　factors　that　lead　to　accidents　and　the　critical　equipment　that　contributes　to　the　initiation　or　propagation　of　domino　effects　can　be　identified.　Moreover,　the　failure　probability　of　different　equipment　exposed　to　possible　accidents　can　also　be　obtained,　supporting　safety　management　of　HRS.