In order to reduce the impact of source load uncertainty on the safe and stable operation of active distribution networks

this paper constructs a multi-time scale optimization model of active distribution network based on distributionally robust optimization.First

model predictive control(MPC)is introduced into the research of distribution network optimization

transforming the original open-loop distribution network optimization into a closed-loop operation through online rolling optimization and feedback adjustment.Then

in the day-ahead optimization

a scene generation method based on Copula theory is used to describe the uncertainty of the scenery;In the intra-day optimization

the probability fuzzy set based on Wasserstein distance is constructed

and the limit scenario method is used to modify it

and the distributed robust optimization(DRO)model is established;In the real-time optimization

the MPC model is corrected by feedback.Finally

a numerical example is given to demonstrate the effectiveness of the model in reducing voltage violations and system operating costs.