Application case of fault location device for distribution network lines

1、 System Overview

The precise fault location system for distribution network lines is widely used for accurate fault location and identification of 10kV-35kV voltage level distribution network lines. Based on advanced technologies such as megawatt level high-speed sampling, Beidou high-precision timing, and precise calibration of signal phase errors, precise positioning of distribution network faults can be achieved. The core module based on artificial intelligence deep learning algorithm can automatically and quickly identify fault types, and assist distribution network operation and inspection personnel in analyzing the causes of faults and warning of hidden dangers.

2、 System architecture

Traveling wave positioning and warning device for distribution network faults

matchNetwork diagnostic deviceBy high-speed collection of fault traveling wave signals and fault power frequency signals in the distribution network, real-time uploading to the monitoring platform, and using artificial intelligence deep learning algorithms for fault diagnosis and output diagnosis results, the diagnosis results are pushed to the operation and maintenance personnel in the form of alarm messages. Relevant information can be viewed in real time through mobile SMS and web client.

IIITraveling wave positioning and warning device for distribution network faultsFeatures

1High precision fault locationBy installing mainline positioning devices and section positioning devices on the main and branch lines of the distribution network, faults on the lines can be quickly located, achieving a distribution network fault positioning accuracy of less than 100 meters;

2Accurate fault recording and traveling wave recordingReal time high-speed sampling, accurate recording of fault current and traveling wave current, providing high-quality data for fault analysis;

3Artificial intelligence fault recognitionThe fault recognition program using artificial intelligence deep learning algorithms has a recognition rate of over 95% for fault types and a fault recognition time of less than 5 minutes;

4Power quality monitoring and alarmReal time monitoring of installation point current, frequency, and harmonics, synchronous calculation of three-phase imbalance of the line, and rapid alarm when exceeding the threshold range; Real time monitoring of overloaded and overloaded lines to prevent potential problems;

5Remote data communication：The distribution network monitoring terminal adopts 4G/VPN power private network communication method to achieve remote transmission and communication of local data, and can perform parameter configuration, remote upgrade and other operations on the terminal through the Dunheng Power Internet of Things platform;

6environmental monitoring：Real time monitoring of environmental parameters such as temperature, sag, dancing, vibration, and tilt of overhead power lines.