Abstract: With the large-scale popularization and application of electric vehicles, the coupled operation characteristics of the transportation network and distribution network are becoming increasingly significant. In this context, a large number of uncertainties will be propagated along with the interaction process of the coupled system, and affect the safe operation of the transportation network and distribution network. For the quantification of the influence of uncertain factors, an analysis method of probabilistic joint flow for transportation network and distribution network considering multiple uncertainties of road-vehicle-sourceload. First, a probabilistic traffic assignment model of the transportation network and a probabilistic optimal power flow model of the distribution network are established, respectively. A decentralized iterative algorithm based on Monte Carlo simulation in an equilibrium state is proposed for probabilistic joint flow computation. Then, the global sensitivity analysis method based on Sobol’method is introduced to quantify the influence of multiple uncertainties of road-vehicle-source-load on the coupled operation state variables of the transportation network and distribution network, and identify the uncertainties that significantly affect the probabilistic joint flow distribution of the transportation network and distribution network. Finally, the proposed method is applied to a coupled case system of the transportation network and distribution network and its effectiveness is verified by simulation results.