•  
  •  
 

Keywords

distribution automation switch cabinet, fuzzy C-means clustering, grey correlation, fault diagnosis

Abstract

This paper proposes a fault diagnosis method for distribution automation switch cabinet based on the Fuzzy C-means (FCM) clustering and gray correlation, aiming at exploring the effect of the distribution automation switch cabinet fault diagnoses on the safety and reliability of distribution networks. Firstly, through various telemetry information, the membership function is calculated, the weight is determined by the AHP-entropy method, and thus the evaluation of hierarchical fuzzy operations of the distribution automation switch cabinet state can be completed. Moreover, according to the typical information of the distribution automation switch cabinet faults, the gray correlation analysis combined with the FCM method are applied to diagnose six common types of fault, which can greatly reduce the calculation complexity and ensure the diagnosis accuracy simultaneously. A case study based on the distribution automation switch cabinet faults in a certain area of Beijing are presented, where the proposed method is compared with the traditional gray correlation analysis. The status evaluation and fault diagnosis results show that the accuracy of the proposed method can reach 90%, which can support the fast, accurate and objective real-time monitoring of distribution automation switch cabinet status and the further development of smart grid automation.

DOI

10.19781/j.issn.1673-9140.2021.02.013

First Page

107

Last Page

115

Download

Share

COinS