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Method and system for determining fault characteristics of active power distribution network

A distribution network fault and determination method technology, applied in the direction of electrical components, circuit devices, electrical digital data processing, etc., can solve the problems of high working ability requirements of maintenance personnel, limited accuracy of results, and occurrence of faults, and achieve fault characteristic variables Reasonable and reliable, high adaptability, and the effect of reducing labor intensity

Pending Publication Date: 2020-02-04
CHINA ELECTRIC POWER RES INST +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] At present, the distribution network with a large number of distributed power sources and two-way flow of power is called an active distribution network. The equipment in the active distribution network may have a tendency to fail due to some external factors under long-term operation, or some Although some equipment can still operate normally after multiple disturbances or failures, the equipment may already have some defects due to cumulative effects
For these potential safety hazards, they are basically avoided through the measurement of the maintenance personnel, which requires high working ability of the maintenance personnel, and the workload is heavy, so the accuracy of the results is limited

Method used

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  • Method and system for determining fault characteristics of active power distribution network
  • Method and system for determining fault characteristics of active power distribution network
  • Method and system for determining fault characteristics of active power distribution network

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Embodiment 1

[0065] Such as figure 1 As shown, a method for determining fault characteristics of an active distribution network provided by the present invention includes:

[0066] S1. Generate sample data based on the acquired historical operation data;

[0067] S2. Using a support vector machine model-recursive feature elimination algorithm to perform feature selection on the sample data and extract fault features;

[0068] S3. Bring the data corresponding to the fault characteristics in the sample data into the fault prediction model based on the support vector machine, and determine the fault prediction accuracy rate of the fault prediction model. When the fault prediction accuracy rate meets the requirements, the The fault feature is set to the fault feature of the active distribution network, otherwise execute S1 to regenerate sample data.

[0069] by figure 2 The specific determination method shown specifically explains the fault characteristics of the active distribution networ...

Embodiment 2

[0158] Based on the same inventive concept, the present invention also provides a system for determining fault characteristics of an active distribution network, including:

[0159] A generating module, configured to generate sample data based on acquired historical operating data;

[0160] An extraction module, configured to use a support vector machine model-recursive feature elimination algorithm to perform feature selection on the sample data and extract fault features;

[0161] The prediction module is used to bring the data corresponding to the fault characteristics in the sample data into the fault prediction model based on the support vector machine, and determine the fault prediction accuracy of the fault prediction model. When the fault prediction accuracy meets the requirements, then Set the fault feature as the fault feature of the active distribution network, otherwise perform S1 to regenerate sample data.

[0162] In an embodiment, the generating module includes...

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Abstract

The invention discloses a method and a system for determining fault characteristics of an active power distribution network. The determination method comprises the steps of S1, generating sample databased on acquired historical operation data; S2, performing feature selection on the sample data by using a support vector machine model-recursive feature elimination algorithm, and extracting fault features; S3, substituting the data corresponding to the fault features in the sample data into a fault prediction model built based on a support vector machine, determining the fault prediction accuracy of the fault prediction model, setting the fault feature as the fault feature of the active power distribution network when the fault prediction accuracy meets the requirement, or otherwise, executing the step S1 to regenerate the sample data. According to the fault feature determination method provided by the invention, the prediction efficiency of the fault prediction model is improved, a reference is provided for power distribution network operation and maintenance personnel, and the labor intensity of the maintenance personnel is reduced.

Description

technical field [0001] The invention relates to the technical field of distribution network operation control, in particular to a method and system for determining fault characteristics of an active distribution network. Background technique [0002] In recent years, as the living standards of urban and rural residents have improved significantly, people's requirements for the reliability of distribution network power supply have been increasing. However, the power part can only passively respond to distribution network failures, which makes the improvement of distribution network reliability a bottleneck. The realization of distribution network fault prediction can provide power sector with decision support for distribution network operation and maintenance, which has significant economic and social benefits. [0003] At present, the distribution network with a large number of distributed power sources and two-way flow of power is called an active distribution network. The ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/215G06K9/62H02H1/00H02H7/28
CPCG06F16/215H02H1/0092H02H7/28G06F18/23213
Inventor 董伟杰刘科研盛万兴孟晓丽贾东梨何开元胡丽娟白牧可叶学顺赵伟陈昶宇
Owner CHINA ELECTRIC POWER RES INST
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