Topology Identification of Low-Voltage Power Lines Based on IEC 61850 and the Clustering Method

Lingyan Sun, Yu Chen (), Qinjun Du, Rui Ding, Zhidong Liu and Qian Cheng
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Lingyan Sun: College of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China
Yu Chen: College of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China
Qinjun Du: College of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China
Rui Ding: College of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China
Zhidong Liu: College of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China
Qian Cheng: College of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China

Energies, 2023, vol. 16, issue 3, 1-20

Abstract: The large-scale access of distributed power puts forward higher requirements for the monitoring of the distribution networks, and the topology identification of low-voltage power lines can effectively promote the integration of monitoring data and the distribution network information, effectively realizing the rapid identification of faults and ensuring the safety of users. In this paper, the method of graph theory was used to simplify the analysis of low-voltage lines, and the full topology identification strategy was proposed. Based on IEC 61850 SCL topology configuration information, line topology identification within the region was realized, and the correlation between regions was determined by the injection method. According to the configuration information, regional association information, and user’s collection information, the low-voltage station area line topology was divided into known regional topology and unknown regional topology. Aiming for the identification of line topology in the unknown region, according to the similarity of voltage fluctuations over short electrical distances, clustering analysis of user’s voltage data in the unknown region was carried out based on the k-means clustering algorithm. The test results showed that this scheme can realize the identification of topology in the region.

Keywords: low-voltage distribution network; line topology identification; graph theory; IEC 61850; SCL; k-means clustering (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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