With the rapid development of photovoltaic power generation,the relativity and uncertainty of power system operation are intensified.In this paper,a hybrid copula dependent probabilistic sequence operations is proposed and applied to the dynamic probabilistic power flow method.Firstly,the PV output is classified according to time interval and the non-parametric kernel density estimation is used to construct the edge probability density of the photovoltaic output,then the single or hybrid copula function is selected according to the characteristics of the photovoltaic output in different time interval s to construct the joint distribution of PV output.Secondly,it is proposed that the hybrid copula dependency sequence operation is combined with the linearization of the traditional power flow equation to obtain the node voltage and power flow distribution.Finally,the IEEE34 node is selected to verify the algorithm.Simulation shows that:selecting the appropriate copula function and classifying the photovoltaic output by time interval,can establish a more accurate probability density function;Selecting a reasonable serialization step results the same computational accuracy as the Monte Carlo simulation method(MCSM),and can shorten the computation time.