Distribution network high-resistance fault location and simulation method based on integrated empirical model decomposition

Abstract

The invention relates to a method for locating and simulating high-resistance faults in distribution networks based on integrated empirical model decomposition, comprising the following steps: collecting phase voltage and phase current at measurement points, calculating zero-sequence voltage and zero-sequence current; adopting integrated empirical model decomposition The method decomposes the zero-sequence voltage and zero-sequence current, and screens a series of eigenmode components reflecting the characteristics of transient faults; according to the eigenmode components, respectively calculates the zero-sequence voltage spectrum and the zero-sequence current quantity spectrum, Realize the determination of high-resistance fault location in distribution network. The present invention uses the integrated empirical mode decomposition method to discretely analyze the zero-sequence voltage of each busbar and the zero-sequence current of each feeder line obtained by the acquisition and transformation, and the calculation speed is fast. Random factors such as resistance and fault time.

Description

technical field [0001] The invention relates to the field of fault location, in particular to a distribution network high-resistance fault location method and a location simulation method based on integrated empirical mode decomposition. Background technique [0002] In the power distribution system, single-phase ground fault is the main form of grid operation fault, and even most phase-to-phase faults are developed from single-phase faults. The types of single-phase ground faults are divided into metallic grounding and high-resistance grounding. When a high-resistance grounding fault occurs, the three-phase line voltage is almost symmetrical, and the fault current is small, and the fault characteristics are not obvious. It is difficult to accurately determine the characteristic quantity. The extraction of high-resistance faults increases the difficulty of high-resistance fault detection. High-resistance grounding faults will affect the normal operation of the power transmi...

AI Technical Summary

Problems solved by technology

The types of single-phase ground faults are divided into metallic grounding and high-resistance grounding. When a high-resistance grounding fault occurs, the three-phase line voltage is almost symmetrical, and the fault current is small, and the fault characteristics are not obvious. It is difficult to accurately determine the characteristic quantity. The extraction of high-resistance faults increases the difficulty of high-resistance fault detection

High-resistance grounding faults will affect the normal operation of the power transmission and distribution system. For arcing grounding faults, due to free air, the grounding impedance changes greatly, causing the existing protection to start and restore repeatedly, which may lead to protection of adjacent lines and equipment. Leapfrog tripping, causing more serious failures in the power system

When the power supply is restored to the user due to a power failure, the high-impedance fault will cause serious consequences such as fire, personal electric shock, etc., and bring losses to life and property. Therefore, the detection of high-impedance faults is very important.

[0003] At present, the research on high-resistance grounding faults mainly focuses on high-resistance grounding protection of lines. There are literatures that use the third harmonic of line current to detect high-impedance faults accompanied by arcs, and there are also methods that use Kalman filter method to study high-resistance grounding faults. In addition, artificial neural networks have also been tried for high-resistance fault detection, but because neural networks require a large number of training samples, it is currently difficult to apply them in the actual power system.

[0004] The integrated empirical mode decomposition is different from FFT, wavelet decomposition, etc. The integrated empirical mode decomposition method does not need to select the basis function, and its decomposition is completely based on the distribution of the extreme points of the signal itself. Through multiple screening, the signal is decomposed into a single one of multiple representative signals. The eigenmode component (Instrinsic Mode Function, IMF) of the mode and a trend item have attracted widespread attention at home and abroad. However, when the distribution of extreme points of the signal is uneven, the decomposition result of the integrated empirical mode decomposition will appear "overshoot" , "undershoot" phenomenon, leading to pattern confusion

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