Abstract: With the increasing penetration of renewable energy in the distribution network, the phenomenon of curtailment caused by its output uncertainty is becoming more and more serious. To solve this problem, a collaborative optimization method for dynamic reconfiguration of the distribution network and mobile energy storage is proposed in the background of high proportion of renewable energy. Firstly, in order to reduce the scale of the problem, the prior information of time series load is fused, and the fuzzy C-means algorithm is used to divide the reconstruction period, while avoiding redundant switching operation. Secondly,considering the uncertainty of renewable energy output, an uncertain set with spatiotemporal correlation and robustness to sparse outliers is constructed. Then, a two-stage robust collaborative optimization model of dynamic reconfiguration strategy and economic dispatch of mobile energy storage is established. In the first stage, the key switch and charging and discharging power stations are selected. In the second stage, the reconfiguration of switches and mobile energy storage are co-optimized to evaluate the economy of the scheme selected in the first stage. Aiming at the complexity of the multi-layer structure of the model, a nested column constraint generation algorithm is used to solve the problem. Finally, the effectiveness of the proposed model and algorithm is verified by simulation in the test system.