Method for acquiring excitation current characteristic quantities of transformer online

Abstract

The invention discloses a method for acquiring excitation current characteristic quantities of a transformer online. The method comprises the steps of A, performing experimental acquisition of neutralpoint direct current and excitation current characteristic quantity sample data of the transformer; B, training a neural network; and C, acquiring the excitation current characteristic quantities ofthe transformer online. According to the invention, the direct current component of the neutral point current of the transformer can be measured online, four types of characteristic quantities, namely, the direct current component, the maximum value, the minimum value and the total harmonic distortion rate of the excitation current of the transformer can be calculated by fitting through utilizinga neural network algorithm, and a clear relationship between the excitation current characteristic quantities and the neutral point direct current of the transformer can be obtained, data support andguidance can be provided for analysis and suppression of direct current magnetic bias of the transformer, and the method has high engineering application value.

Description

technical field [0001] The invention belongs to the technical field of power system detection, and in particular relates to an online acquisition method for transformer excitation current characteristic quantities. Background technique [0002] During the operation of urban rail transit, unipolar operation of HVDC power transmission system or geomagnetic storm, DC current will flow into the neutral point of transformer, which will cause distortion of transformer excitation current, that is, DC bias phenomenon of transformer. The actual operation case shows that the DC bias of the transformer mainly has the following hazards: [0003] (1) The DC bias will make the transformer work in an oversaturated state, which will cause the deformation of the transformer core, causing the transformer to vibrate and generate noise. [0004] (2) The DC bias will cause the output current of the transformer to be distorted, which will cause the malfunction or refusal of the relay protection....

AI Technical Summary

Problems solved by technology

[0003] (1) DC bias will cause the transformer to work in an oversaturated state, which will cause deformation of the transformer core and cause transformer vibration and noise

[0004] (2) DC bias will cause distortion of the output current of the transformer, which will cause malfunction or refusal of relay protection

[0005] (3) DC bias will increase the magnetic flux leakage of the transformer, resulting in eddy current loss of the transformer, which will generate abnormal heating, damage the transformer components, and reduce the life of the transformer

[0007] Existing research or technology exists on the analysis of transformer excitation characteristics and the acquisition of excitation current. In terms of excitation characteristics analysis, the Chinese patent application number 201510214689.2 proposes a method for analyzing the change of excitation characteristics of transformers under the influence of DC bias. The method is based on the principle of magnetic coupling and Fourier transform to obtain the excitation characteristics of the transformer under DC bias. The relationship between the center point DC current

The Chinese patent application number 201510184067.X proposes a method for determining the hysteresis and loss characteristics of transformers under DC bias state. This method mainly determines the hysteresis and loss characteristics of transformers by establishing a finite element model of the transformer laminated iron core. However, this method cannot obtain transformer excitation current or excitation current characteristic quantity online

In terms of excitation current acquisition, the Chinese patent application number 2015103125304 proposes a transformer excitation current simulation met

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