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Power transmission line fault identification method based on deep learning

A transmission line and deep learning technology, applied in the field of power lines, can solve problems such as low efficiency of fault identification of transmission lines

Pending Publication Date: 2020-12-29
STATE GRID JIANGXI ELECTRIC POWER CO LTD RES INST +2
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Problems solved by technology

[0004] The purpose of the present invention is to propose a transmission line fault identification method based on deep learning in order to solve the technical problem of low efficiency in fault identification of existing transmission lines and realize efficient identification of faults in transmission lines

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  • Power transmission line fault identification method based on deep learning
  • Power transmission line fault identification method based on deep learning
  • Power transmission line fault identification method based on deep learning

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Embodiment Construction

[0070] The embodiments will be described in detail below in conjunction with the accompanying drawings.

[0071] In order to verify the effectiveness of the transmission line fault identification model proposed above and the rationality of parameter settings, the wave recording data of a power company in a certain area is collected to form a test set for verification. The specific method steps are as follows:

[0072] Step 1. Select data from the historical database of the wave recording system to adjust the parameters of the fault classification method. The algorithm of this embodiment uses the wave recording current and voltage, so first convert the wave recording current and voltage sequence of the transmission line from the above wave recording file according to the established data conversion rules; then generate the current and voltage sequence text, and the sequence data acquisition The interval is 0.3125ms, that is, 3200 equally spaced data are collected per second. ...

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Abstract

The invention provides a power transmission line fault identification method based on deep learning. The method comprises the steps of extracting fault current and voltage signals in a wave recordingsystem; extracting and analyzing feature information of the fault current and voltage signals by adopting a Fourier analysis technology; then calculating fundamental components and third harmonic components of zero-sequence current and zero-sequence voltage; and finally, performing specific fault identification according to a classification model. According to the judgment method, a linear classification module and a nonlinear classification module are involved, wherein linear classification is that data samples are preliminarily classified through the zero-sequence current and the zero-sequence voltage; and on the basis, according to data characteristics of power transmission line faults, multiple types of fault data are classified by selecting deep learning, and finally power transmission line fault identification is realized.

Description

technical field [0001] The invention relates to a transmission line fault identification method based on deep learning, which belongs to the technical field of power lines. Background technique [0002] The geographical environment of my country's transmission lines is relatively harsh, and the transmission network covers a wide area. Some lines may pass through mountains, rivers, seas, plains and other landforms. , prone to tripping accidents. [0003] After a fault occurs, the power company will arrange personnel to inspect the line within the range of fault distance measurement and location to find out the specific cause of the fault, and then organize professionals to repair the fault. However, transmission line faults often occur in suburban areas, and it may take several hours from tripping to restore the normal power supply of the line, which will have a great impact on the social economy and people's lives. If after the line trips, the possible cause of the fault ca...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/08G01R27/08G01R23/16G01R31/52G06N20/00
CPCG01R31/08G01R31/088G01R31/52G01R27/08G01R23/16G06N20/00
Inventor 周龙武张宇陆帅杨胡萍邹建章廖豪爽胡京饶斌斌况燕军李帆
Owner STATE GRID JIANGXI ELECTRIC POWER CO LTD RES INST
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