A Fault Diagnosis Method of Active Distribution Network Based on Fault Search Table and Data Mining Technology

Abstract

Centralized feeder automation has high flexibility and adaptability and is suitable for various distribution system. In this paper, the fault search table is established based on fault information, then we use Aprion data mining technology to analyze the fault search table to locate the fault. This location method can be applied to centralized feeder automation. At the same time, considering the misjudgement caused by lost information and distorted information at special locations, combined with this method and the result of secondary positioning, a method which can accurately relocate and close the wrong actuating switch is designed to reduce the blackout range. Finally, by comparing the suspicious failure set and its elements, the lost information and distorted information in the system can be found. The fault diagnosis method has the advantages of simple principle and high expandability. It can quickly and automatically obtain a malfunction report when a fault occurs, and has relatively high fault tolerance. This is helpful for the development of centralized feeder automation and the development of self-healing power grid.