Single-phase earth fault research and judgment method based on multi-algorithm normalization analysis

A single-phase ground fault and normalization technology, applied in the field of distribution network, can solve problems such as line tripping, endangering system insulation and equipment safety, and power outages for users

Inactive Publication Date: 2020-11-06
NARI TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the increase of the non-fault phase-to-ground voltage when grounding, especially when there is an intermittent arc-fault grounding fault, arc overvoltage will be generated, which seriously endangers system insulation and equipment safety.
At the same time, the overvoltage may cause the ground fault to be transformed into a phase-to-phase short circuit fault, tripping the line and causing power outages for users

Method used

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  • Single-phase earth fault research and judgment method based on multi-algorithm normalization analysis
  • Single-phase earth fault research and judgment method based on multi-algorithm normalization analysis
  • Single-phase earth fault research and judgment method based on multi-algorithm normalization analysis

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Embodiment 1

[0033] Embodiment 1. A single-phase ground fault research and judgment method based on multi-algorithm normalization analysis, comprising the steps: step 1, using the pre-trained deep learning model to analyze the working condition data (i.e. data The operating condition data obtained by image feature extraction) is used for fault identification to determine whether a fault occurs; step 2, using the pre-trained decision tree to identify multiple operating condition types for the operating condition data that is determined to have a fault.

[0034] 1) Input data image feature extraction

[0035] The selected input signal is the A, B, C three-phase current waveform on the line, and the waveform length is the data from 4 power frequency cycles before the fault occurs to 8 power frequency cycles after the fault occurs. To visualize the input data, the waveform sequence must first be matrixed. Calculated at a sampling rate of 1K, the input waveform sequence is a=[1×3072]-dimension...

Embodiment 2

[0051] Embodiment 2. On the basis of Embodiment 1, this embodiment also includes the steps of result verification after the obtained multi-working-condition type discrimination results, including:

[0052] The fault recognition rate, an evaluation index in traditional pattern recognition, is introduced, and its calculation method is as follows:

[0053]

[0054] In the formula: T is the input known failure test sample set; C is the number of correctly identified samples in the set.

[0055] In order to reflect the recognition stability of the model for various fault signals, the evaluation index of wrong (missing) fraction rate is introduced, and its calculation method is as follows:

[0056]

[0057] In the formula: N is the set of various fault test samples input; M is the number of wrong (missed) samples in the set.

[0058] The test uses a variety of different types of faults (including grounding, short circuit, inrush current, accumulation, power recovery, and powe...

Embodiment 3

[0067] Embodiment three, as image 3 As shown, on the basis of the above embodiments, this embodiment provides a single-phase ground fault research and judgment method based on multi-algorithm normalization analysis, which also includes the following steps after completing the identification of multiple working conditions:

[0068] According to the model and classifier formed in step 1 and step 2, the incoming waveforms are matched and analyzed one by one, and the steady-state data of the real-time system is superimposed at the same time for multi-algorithm normalization analysis, and the fault identification results obtained by classifying steps 1 and 2 are used , using steady-state information such as voltage, current, and network topology to conduct comprehensive analysis, form fault intervals and form operable fault handling strategies, and complete all fault research and judgment logics.

[0069] The specific analysis method is as follows:

[0070] a) Obtain the waveform...

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Abstract

The invention discloses a single-phase earth fault research and judgment method based on multi-algorithm normalization analysis, and the method comprises the steps of carrying out the fault recognition of working condition data of a selected time period under a selected bus through a pre-trained deep learning model, and determining whether a fault happens or not; and utilizing a pre-trained decision tree to carry out multi-working-condition type discrimination on the working condition data which is determined to have the fault. The invention assists dispatchers in quickly positioning the single-phase grounding of the power distribution network to form an operable result, and provides a basis for improving the fault processing efficiency of the dispatchers and guaranteeing the operation stability of the power distribution network.

Description

technical field [0001] The invention relates to the technical field of distribution networks, in particular to a method for researching and judging single-phase grounding faults based on multi-algorithm normalization analysis. Background technique [0002] The medium-voltage distribution network in my country widely adopts the non-effective neutral point grounding operation mode, mainly including the neutral point non-grounding mode and the arc-suppression coil grounding mode. Compared with the high-voltage transmission network, the probability of failure in the medium-voltage distribution network is much higher, especially the single-phase ground fault occurs frequently. Statistics show that the single-phase ground fault accounts for about 80% of the total distribution network faults. When a single-phase ground fault occurs in a distribution network with a neutral point non-effectively grounded operation mode, a short-circuit loop will not be formed, and only a small ground...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08G01R31/08G01R31/52
CPCG06N3/084G01R31/086G01R31/088G01R31/52G06N3/045G06F2218/12G06F18/24323G06F18/214
Inventor 时金媛张蓓蓓苏标龙苏光
Owner NARI TECH CO LTD
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