Novel method for identifying overvoltage inside distribution network

An identification method and overvoltage technology, applied in the field of distribution network, can solve problems such as difficult identification of high-dimensional features, achieve the effects of avoiding subjectivity and complexity, improving speed and accuracy, and overcoming low accuracy

Active Publication Date: 2019-01-04
FUZHOU UNIVERSITY
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Problems solved by technology

This type of shallow classifier has a good recognition effect on low-dimensional features, bu

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  • Novel method for identifying overvoltage inside distribution network
  • Novel method for identifying overvoltage inside distribution network
  • Novel method for identifying overvoltage inside distribution network

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Embodiment Construction

[0037] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0038] The present invention provides a novel internal overvoltage identification method of a distribution network, comprising the following steps:

[0039] Step S1, after an overvoltage occurs in the distribution network, the waveform sampling data of the three-phase voltage of the busbar within a period of time before and after the occurrence of the overvoltage is obtained to obtain voltage data;

[0040] Step S2, performing atomic decomposition on the voltage data obtained in step S1 to obtain the optimal atom and its parameters;

[0041] Step S3, reconstructing the optimal atoms obtained in step S2 into each sub-frequency band according to frequency, to obtain a time-frequency matrix;

[0042] Step S4, summing the time-frequency matrix in blocks, and splicing according to the phases to obtain the three-phase characteristic atomic spe...

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Abstract

The invention relates to a novel method for identifying overvoltage inside a distribution network. An atomic decomposition algorithm optimized based on an imperial colonial competition algorithm is applied to the analysis of over-voltage signals, and the optimized algorithm can be used to extract the internal characteristics of signals quickly and effectively without being disturbed by noise. A three-phase characteristic atomic spectrum is constructed based on the atomic decomposition algorithm, waveform signals only containing time-domain information are converted into high-dimensional characteristics containing time-frequency information, and the time-frequency characteristics of overvoltage signals are described completely. The three-phase characteristic atomic spectrum is recognized directly by using a convolution neural network, the shortcomings of a shallow learning identification algorithm for the identification of high-dimensional characteristics are overcome, and the subjectivity and complexity in the process of characteristic reduction are avoided. Simulation waveforms and physical models verify that the distribution network overvoltage type identification method of the invention has high identification accuracy and strong adaptability.

Description

technical field [0001] The invention relates to the field of distribution networks, in particular to a novel internal overvoltage identification method of a distribution network. Background technique [0002] Traditional operating experience and research have shown that overvoltage may cause insulation breakdown of equipment and lines, affect the normal operation of the power system, and eventually bring huge economic losses and personal hazards. According to statistics, overvoltage accidents in the distribution network account for about 70% to 80% of the overvoltage accidents in the entire power system. Quickly and accurately identifying the type of overvoltage will help engineers and technicians find out the cause of the accident in a timely manner and provide a basis for proposing The voltage suppression method and the improvement of distribution network insulation coordination provide a basis, which is of great significance for improving the self-healing ability of distr...

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Application Information

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IPC IPC(8): G01R19/165G06N3/04
CPCG01R19/16576G06N3/045
Inventor 杨耿杰廖宇飞高伟郭谋发
Owner FUZHOU UNIVERSITY
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