Topology Identification of Medium Voltage Distribution Network Based on Copula Entropy

In order to solve the problems of frequent changes in distribution network topology and difficult topology identification, a topology identification method for medium voltage distribution network based on Copula entropy (CE) is proposed. First, a Copula function containing multivariable dependencies is established. Second, the CE defined by the Copula function is estimated by using the nonparametric method to obtain the Copula entropy correlation matrix between nodes. Finally, the maximum spanning tree algorithm is used to complete the topology identification of the medium voltage distribution network. The method measures the precision of the dependency of global variables, and the measured dependency is not related to the attributes of a single variable, and the local optimal problem is avoided. At the same time, this method has no linear and Gaussian assumptions, which is more conducive to the application in the actual distribution network in the future. The effectiveness and robustness of the proposed method are verified by IEEE33 bus distribution network simulation, and it shows some advantages over the existing methods.

Automated summary

This study proposes a topology identification method for medium voltage distribution network based on Copula entropy. It aims to solve the problems of frequent changes in network topology and difficult identification. The method effectively measures the dependency of global variables without linear and Gaussian assumptions, and demonstrates its effectiveness and advantages through simulation.