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Distribution network fault location method utilizing natural frequency and artificial neural network

A technology of artificial neural network and fault location, which is applied in the direction of biological neural network model, fault location, etc., to achieve good robustness

Active Publication Date: 2011-07-20
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

The present invention uses neural network for fault distance measurement

Method used

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  • Distribution network fault location method utilizing natural frequency and artificial neural network
  • Distribution network fault location method utilizing natural frequency and artificial neural network
  • Distribution network fault location method utilizing natural frequency and artificial neural network

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Embodiment Construction

[0062] Specific simulation models such as figure 2 As shown, take a fault point every 50m on the line, that is, Δ l =50m, the fault resistance is 20Ω, and the fault closing angle θ=0°, 30°, 45°, 60°, 90°, the simulation is carried out.

[0063] (1) After a single-phase ground fault occurs in the distribution network, the starting element starts immediately, and the zero-sequence current fault component of the fault can be obtained according to the three-phase current measured at the protection installation for:

[0064] (1)

[0065] where, are the three-phase currents of fault lines A, B, and C respectively, k =1, 2, 3... N , N is the length of the sampling sequence;

[0066] (2) Perform FFT transformation on the transient zero-sequence current of the fault line. The sampling frequency is 1MHz and the sampling length is 2048. After FFT transformation, a 2048×2 matrix is ​​obtained:

[0067] (2)

[0068] In the formul...

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Abstract

The invention discloses a distribution network fault location method utilizing a natural frequency and an artificial neural network. In the method, fault location is performed by utilizing a principle that main natural frequencies of a line of a fault traveling wave are different when the line fails at different points; and simultaneously data processing is performed by utilizing a hierarchical distributed artificial neural network. After the line causes a single-phase ground fault, the sampling frequency is 1 MHz; a discrete zero-sequence transient signal with the sampling length of 2048 after the fault is selected; fast Fourier transform (FFT) is performed, wherein the transform result is a matrix of 2048*2; and an absolute value of the matrix is solved. According to the model adopted by the method, the fault location is performed by selecting 8 frequency values with large amplitude values as the sample attribute of the neural network, selecting a suitable transfer function and a learning rule, and setting appropriate neural network parameters to construct a back propagation (BP) network model. A large number of simulation results show that the method has a good effect.

Description

technical field [0001] The invention relates to the technical field of electric power system relay protection, in particular to a distribution network fault ranging method using natural frequency and artificial neural network. Background technique [0002] At present, the existing distribution network ranging methods include "S" injection method, differential equation method, traveling wave method and parameter identification method. The "S" injection method is to calculate the fault impedance from the busbar to the fault point by detecting the current and voltage of the fault line injection signal, and calculate the fault point position based on the known impedance per unit length. However, the sensitivity of this method is easily affected by the injected signal, and the positioning effect is related to the actual operation situation in the field. The differential equation method uses the transient differential equations of some lines to use the measured transient voltage ...

Claims

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Application Information

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IPC IPC(8): G01R31/08G06N3/02
Inventor 束洪春段锐敏田鑫萃王旭邬乾晋秦书硕张广斌刘可真孙士云
Owner KUNMING UNIV OF SCI & TECH
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