The AC/DC hybrid distribution system with multi-terminal flexible DC has many advantages in terms of flexibility and power regulation

but the introduction of flexible DC also leads to the risk coupled between the AC and DC system

meanwhile

after the complex control modes of flexible DC are taken into consideration

the risk assessment and operation optimization of the AC/DC hybrid distribution system face new challenges. Consequently

an effective point estimation-based risk assessment method

in which the voltage source converter control mode and the impact of AC and DC risk coupling

are fully taken into consideration is proposed. In the proposed method

only a small number of power flow calculation of the estimation points that are constructed from the center distance and second-order moments of random input variables needs to perform. Therefore

the probability distribution of the output state variables is effectively estimated and risk assessment is realized. On this basis

a multi-objective risk scheduling model focusing on minimizing both the operational risk and expected network power loss is established

and an improved kriging surrogated model assisted multi-object grey wolf algorithm is proposed to solve the model. Due to a large-scale Pareto solution and difficulty in making fast decisions

a fuzzy clustering method is proposed to quickly find the optimal Pareto solution. Case study is performed on an AC/DC hybrid system with three AC networks and one DC network. The results show that the proposed method can be adopted to greatly improve the evaluation efficiency compared with the traditional Monte Carlo sampling method. Also

the operational risk can be effectively reduced and the reliability is greatly improved.