Distribution Network Topology Identification Based on Time Series Voltage Mutual Information and Probability Density Function

Recognition of distribution network topology is usually based on switching and node related data. It is difficult to frequently interact with multi-dimensional and real-time data, but the reliability of the identification is not high only by uploading the switching quantity. In this paper, a topology identification method based on node voltage magnitude is investigated to accurately recognize the topology of distribution networks. First., take the example of a radial distribution network., mutual information is used to analyze the similarity of two nodes' timing voltages. Then., probability density distribution curves are used to determine whether multiple nodes are in the same branch. Next., the topology identification process is proposed: monitoring whether the topology is changed., determining which branch is disconnected., determining the exact location of the breakpoint., verifying whether the switch is correct., and reconstructing the topology. Finally., the IEEE33 node system is taken as an example and simulated in MATLAB for verification. The topology derived from the identification is accurate., proving the effectiveness of the method.