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Transient state power quality disturbance classification recognition method based on BUD spectrum kurtosis

A technology for transient power quality and classification recognition, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as not found, reduce vector dimension, improve classification speed and accuracy, and suppress cross-terms interference effect

Inactive Publication Date: 2012-10-24
SOUTHWEST JIAOTONG UNIV
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AI Technical Summary

Problems solved by technology

For the feature extraction of disturbance signals, a particularly suitable method has not yet been found, and the use of various new methods is also being explored

Method used

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  • Transient state power quality disturbance classification recognition method based on BUD spectrum kurtosis
  • Transient state power quality disturbance classification recognition method based on BUD spectrum kurtosis
  • Transient state power quality disturbance classification recognition method based on BUD spectrum kurtosis

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specific Embodiment approach

[0059] figure 1 Shown, a kind of embodiment of the present invention is: a kind of transient electric energy quality classification identification method based on BUD spectral kurtosis, and its concrete practice is:

[0060] A. Extract the disturbance characteristic signal

[0061] figure 2 A schematic diagram showing the establishment of a transmission line model using PSCAD / EMTDC. The power supply E1, E2 is 220KV, and the phase angle is zero; A1, A2, A3 are bus bars; B1, B2, B3, B4 are circuit breakers; C1, C2, C3 are ground capacitances.

[0062] (1) Generate a pulse transient. Add a controlled current source whose control source is lightning current at point M to simulate lightning strike phenomenon and obtain pulse transient signal.

[0063] (2) Oscillation transients are generated. A 1uF grounded capacitor C3 is put into the bus A3 to obtain an oscillating transient signal.

[0064] Use PSCAD / EMTDC to generate simulation signals, but the disturbance signals actual...

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Abstract

The invention relates to a transient state power quality disturbance classification recognition method based on BUD spectrum kurtosis. The method adopts the BUD spectrum kurtosis method to calculate kurtosis of two disturbing signals of transient state pulse and transient oscillation, selecting maximum value, minimum value and average value of the kurtosis as characteristic quantity and inputting SVM of PSO optimizing parameters to conduct practice tests. Simulation data are obtained through PSCAD / EMTDC, and the method is used for conducting analysis. Results show that the method based on the BUD kurtosis is capable of effectively extracting disturbance characteristic quantity and has good noiseproof performance. An SVM classifier can be used for recognizing two disturbances when small samples are overlapped with other disturbances, and recognition rate is high.

Description

technical field [0001] The invention relates to the intelligent monitoring of power systems, in particular to the technical field of classification and identification of transient power quality based on BUD spectral kurtosis. Background technique [0002] With the continuous expansion of the power system scale and the large investment of various power electronic equipment, nonlinear loads, and impact loads, the gap between the power quality level and the user's requirements is increasing, which seriously affects the quality of industrial products and residents. The problems brought about in daily life have attracted great attention of power workers in various countries, and the quality of transient power has gradually become a common concern of power supply departments and users. Existing devices have obvious limitations in the monitoring and identification of transient disturbances, and there are few monitoring indicators. Most products can only monitor and identify three t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 刘志刚陈刚张巧革
Owner SOUTHWEST JIAOTONG UNIV
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