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A method for identifying fault types in distribution network

A technology for fault and type identification of distribution network, applied in the field of electric power, can solve the problems of loss of effective information, reduced accuracy of classification and identification, and inability to reflect fault information in more detail, so as to improve the degree of detail, classification and accuracy Effect

Active Publication Date: 2022-02-22
BEIJING INHAND NETWORKS TECH
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Problems solved by technology

It can be seen that the setting of the number of features in the prior art is limited when using the feature extraction of fault recordings. When the number of features is too large, it will cause the training of the neural network model to become difficult, and when the number of features is too small, it will lead to The effective information of the waveform is lost, resulting in a decrease in the accuracy of classification and recognition
Moreover, the number of types of fault classification is limited by this method, and the fault information cannot be reflected in more detail.

Method used

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  • A method for identifying fault types in distribution network
  • A method for identifying fault types in distribution network
  • A method for identifying fault types in distribution network

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Embodiment Construction

[0065] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0066] Figure 8 It is the original fault waveform diagram. After collecting 16 cycles of the original fault waveform, with 1312 sampling points, three-phase and zero-sequence 4-phase currents are collected, and the fault waveform matrix is ​​obtained as a 1312×4 matrix.

[0067] Intercept the fault waveform segment P with s=3, p=82 i , then get P 1 to P 411 There are 411 waveform segments in total, and the above 411 waveform segments are sequentially input into the template similarity model with 30 waveform templates, ie d=30. The parameters in the deep neural network in the template similarity model are obtained using the training method of the model of the present invention. When performing model training, the parameters in the loss function are set to γ=0...

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Abstract

The invention discloses a method for identifying fault types of a distribution network, which is characterized in that the method includes: obtaining a fault waveform of a distribution network; performing compression coding on the fault waveform, and the compression coding includes performing The similarity operation and threshold encoding are used to obtain the characteristic compression code of the fault waveform; the characteristic compression code is input into the classification model to obtain the type of the fault waveform of the distribution network.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to a classification method for distribution network fault types. Background technique [0002] The distribution network is an important part of the power system. With the rapid development of the smart grid, a large number of uncertain connections of distributed power sources make the fault information of the distribution network more and more complicated, and the accurate and rapid analysis of the fault becomes more and more difficult. In order to ensure the highly intelligent operation of the distribution network, real-time monitoring of feeder operation data, timely warning of abnormal conditions, and rapid fault detection and processing are required. Among them, the identification of distribution network fault types is an important function of intelligent distribution network. The traditional distribution network fault type identification either uses the expert library t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/08
CPCG01R31/086G01R31/088
Inventor 姚蔷张建良
Owner BEIJING INHAND NETWORKS TECH
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