Power distribution network wire state monitoring method and system based on Beidou positioning

By setting up multiple acquisition points in the distribution network, collecting power waveform changes data in real time, and using Beidou positioning and machine learning analysis, combined with the distribution automation system, the rapid positioning and handling of distribution network faults is achieved, solving the problems of fault positioning difficulties and low efficiency in the existing technology, reducing costs and improving power supply reliability.

CN119716367APending Publication Date: 2025-03-28CHANGSHAN COUNTY POWER SUPPLY CO OF STATE GRID ZHEJIANG ELECTRIC POWER CO LTD
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Patent Information

Application Number
CN202410758283.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-06-13
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

In the prior art, distribution network fault location is difficult, low efficiency, high cost, and there are a large number of hidden faults and long-line fault patrols.

Method used

The distribution network conductor status monitoring method based on Beidou positioning is adopted. By setting up multiple acquisition points on overhead lines, power waveform change data is collected in real time, and Beidou positioning information is obtained. Combined with the deep fusion of machine learning analysis and the distribution automation system, the real-time upload of fault information and the rapid processing of fault analysis and positioning is achieved.

Benefits of technology

It effectively solves the difficulties in fault positioning of distribution networks, reduces manpower and material consumption, improves power supply reliability, and improves fault stability and positioning accuracy through distributed collaboration.

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Abstract

The invention discloses a power distribution network wire state monitoring method and system based on Beidou positioning, and solves the problems of difficult fault positioning, low efficiency and high cost of a power distribution network in the prior art, and the method comprises the steps: setting a collection point at an overhead line, collecting power waveform change data in real time, and obtaining the Beidou positioning information of the collection point; performing machine learning fault analysis according to a historical fault library and the current voltage and current waveform change data, and outputting a fault classification label; fault information is exchanged among the acquisition points in real time, fault positions are positioned through collaborative analysis, and the accuracy of fault analysis results is mutually verified; and calculating a target fault calculation position of the current fault, and judging a fault position point in combination with Beidou positioning information. A traveling wave detection technology, machine learning analysis and a power distribution automation system are seamlessly jointed, real-time uploading of fault information and rapid processing of fault analysis and positioning are realized, manpower and material resource consumption is reduced, and power supply reliability is improved.
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