Due to the scarcity of measurement equipment and the shortage of communication infrastructure

the low measurement coverage and low observability of power distribution networks weaken the accuracy of distribution network state estimation. To overcome the problems of low observability in distribution networks and enhance the effect of state estimation

this paper proposes a data-augmented state estimation for partially visible three-phase distribution networks. First

a measurement data augmentation model of distribution networks based on matrix completion is proposed. The measurement matrix is divided into blocks according to the modularity index

and multiple measurement matrices are completed separately. This method improves the computational efficiency of matrix completion in large-scale systems. Then

a robust state estimation method of three-phase distribution networks based on augmented data information is proposed to solve the problem that the weight coefficient of the generated measurement is difficult to determine. Finally

the effectiveness and practicability of the proposed method are verified through tests on three-phase unbalanced and balanced systems respectively. Numerical results demonstrate that the proposed method can effectively complete the measurement matrix and improve the state estimation accuracy of distribution networks.