Arc light grounding fault distinguishing method based on harmonic wave energy and waveform distortion characteristics

Abstract

The invention discloses an arc light grounding fault distinguishing method based on harmonic wave energy and waveform distortion characteristics. Firstly, waveforms and their harmonic amplitude valuesof three-phase voltage and zero-sequence current of a system are obtained through a power distribution network miniature PMU; the harmonic amplitude values of the waveforms of the three-phase voltageand zero-sequence current are utilized to calculate dimension-unified harmonic energy of each period, and whether the system has suspected arc light grounding faults or not is judged; randomness analysis is conducted on the harmonic energy of each period in a detection window to obtain randomness indexes of the harmonic energy, and it is determined whether identified suspected arc light groundingfaults are mistakenly judged or not; waveform distortion characteristics of stable arcing are extracted by conducting time-frequency domain analysis on the waveforms of the three-phase voltage and zero-sequence current, the influence of the stable arcing process on randomness analysis is avoided, and accordingly mistaken judgement is avoided. The arc light grounding fault distinguishing method accurately extracts arc light grounding fault characteristics and achieves the technical basis of a reliable, safe and quick fault distinguishing algorithm.

Description

technical field [0001] The invention relates to the technical field of ground fault identification, in particular to an arc light ground fault identification method combined with a signal processing mechanism of a micro-PMU of a distribution network and based on the randomness and waveform distortion characteristics of its signal harmonic energy. Background technique [0002] At present, a large number of researches on arc fault identification mainly focus on the analysis of the characteristics of arc stable arcing process. The arc waveform, harmonic, amplitude and phasor characteristics of this process are relatively stable and more prominent, and it is easy to find corresponding methods describe. However, when an actual arc-flash ground fault occurs, it always goes through a period of unstable arcing process first, ranging from a few cycles to 1 to 2 seconds. The unstable arcing process has very strong randomness and nonlinearity, and is accompanied by intermittent arcing...

AI Technical Summary

Problems solved by technology

The unstable arcing process has very strong randomness and nonlinearity, and is accompanied by intermittent arcing phenomenon. Therefore, the fault feature description and extraction method obtained by analyzing the stable arcing process is not completely suitable for unstable arcing process. process

For some unstable arcing processes that take a long time, and even arc ground faults in stable arcing processes do not occur, the reliability and rapidity of the relevant identification methods are difficult to guarantee

[0003] my country's power distribution network is dominated by small-current grounding systems, and the arc-fault ground fault signal is weak. Even in some coastal areas with small-resistance grounding systems, it is still impossible to reliably detect and identify fault types when arc-light high-resistance grounding faults occur

According to statistics, the detection rate of the relay protection devices installed in the distribution network to arc high-resistance faults is less than 20%, which cannot meet the reliability requirements of fault identification, and poses a huge hidden danger to the stable operation of the system and the safety of personnel and property.

[0006] The existing low-current arc-fault identification methods have the following technical problems: (1) At present, a large number of algorithms are aimed at various characteristics in the stable arcing process of the arc, and these characteristics are often not fully applicable in the unstable arcing process; ( 2) The difficulty in feature extraction of arcing ground faults is not only that the features of small current arcing grounding faults (arcing grounding faults in small current grounding systems, arcing high resistance grounding faults in various grounding systems, etc.) are weak and difficult to extract, but also there are The signal characteristics of small-current arc-fault ground faults and large-current arc-fault ground faults are very different, and the identification method needs to meet the extraction requirements of these two types of fault features with a large gap; (4) The existing arc-flash ground fault identification algorithm is mainly based on the local fault information of the distribution network substation, or a self-designed fault signal extraction and identification device, both in terms of reliability and economy In general, the above two methods face great limitations in practical application.

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