To evaluate the impact of the uncertainty of large-scale renewable distributed generation and flexible load on distribution network line congestion, a scheduling management method considering the aversion of different degrees of out of limit risk and the resistance to potential congestion risk outside the confidence interval is proposed based on utility theory and flexibility. The congestion risk assessment model is constructed by integrating the three factors of distribution line congestion probability, congestion severity and risk aversion. The line blocking type is defined by the power transmission direction of the blocking line. The actual impact caused by line blocking is considered in different regions, and the blocking resistance level of the system is reflected in the response degree of the flexible supply capacity of the gas turbine, the energy storage system and the interruptible load to the potential blocking risk outside the confidence interval. The economic benefits of the distribution network are reflected by the network loss of the distribution system, and the scale benefits of distributed generation are presented by the benefits of virtual power plants. A multi-objective optimization model for safe and economic dispatching of the distribution system is constructed. Finally, based on the analysis and verification of the proposed model based on the IEEE33 node system. The results show that the day ahead scheduling scheme based on this method can effectively reduce system congestion risk and enhance the ability to resist potential congestion risk while taking account of economic benefits. This work is supported by the Natural Science Foundation of Fujian Province (No. 2017J01480).