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Voltage sag multiple disturbance source identification method based on pso optimization width learning

A technology of voltage sag and identification method, which is applied in the field of voltage sag multiple disturbance source identification based on PSO optimization width learning, can solve the problems of long identification time, mismatch between extracted features and input, etc., and achieves intuitive identification effect and identification method. Simple and easy to implement, the effect of shortening the identification time

Active Publication Date: 2022-07-12
GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The embodiment of the present invention provides a voltage sag multiple disturbance source identification method, device and equipment based on PSO optimization width learning, which is used to solve the problem that feature extraction and source identification are separate operations in the existing identification method for voltage sag. There are technical problems that the extracted features do not match the input and the recognition time is long

Method used

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  • Voltage sag multiple disturbance source identification method based on pso optimization width learning
  • Voltage sag multiple disturbance source identification method based on pso optimization width learning
  • Voltage sag multiple disturbance source identification method based on pso optimization width learning

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Embodiment 1

[0048] figure 1 This is a flow chart of the steps of the method for identifying multiple disturbance sources of voltage sag based on the PSO optimized width learning according to the embodiment of the present invention.

[0049] like figure 1 As shown, an embodiment of the present invention provides a voltage sag multiple disturbance source identification method based on PSO optimization width learning, including the following steps:

[0050] S1. Acquire the data of the k voltage sag disturbance sources, and process the data of the k voltage sag disturbance sources to obtain reference characteristics of each voltage sag disturbance source.

[0051] It should be noted that the main purpose is to obtain the data of the disturbance sources that cause voltage sags in history, analyze and process the data of different disturbance sources, and obtain the reference characteristics of different disturbance sources, which provide basic data for subsequent identification of the disturb...

Embodiment 2

[0110] Image 6 This is a frame diagram of the apparatus for identifying multiple disturbance sources of voltage sag based on the PSO optimization width learning according to the embodiment of the present invention.

[0111] like Image 6 As shown, the embodiment of the present invention also provides a voltage sag multiple disturbance source identification device based on PSO optimized width learning, including a data acquisition processing module 101, a model building module 102, a training module 103, and an identification module 104;

[0112] The data acquisition and processing module 101 is configured to acquire data of k voltage sag disturbance sources, and process the data of the k voltage sag disturbance sources to obtain reference characteristics of each voltage sag disturbance source;

[0113] The model building module 102 is used to construct a PSO optimized width learning model, and uses the PSO optimized width learning model to process and analyze the reference f...

Embodiment 3

[0118] The embodiment of the present invention provides a voltage sag multiple disturbance source identification device based on PSO optimization width learning, including a processor and a memory;

[0119] a memory for storing program code and transmitting the program code to the processor;

[0120] The processor is configured to execute the above-mentioned method for identifying multiple disturbance sources of voltage sag based on PSO optimization width learning according to the instructions in the program code.

[0121] It should be noted that the processor is configured to execute the steps in the above-mentioned embodiment of the method for identifying multiple disturbance sources of voltage sag based on PSO optimization width learning according to the instructions in the program code. Alternatively, when the processor executes the computer program, the functions of each module / unit in the above-mentioned system / device embodiments are implemented.

[0122] Exemplarily, a...

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Abstract

The invention relates to a voltage sag multiple disturbance source identification method, device and equipment based on PSO optimization width learning. The voltage sag multiple disturbance source identification method based on PSO optimization width learning can avoid data omission and mismatch between extraction and identification. In order to improve the identification efficiency and eliminate the uncertain influence of random weights, the identification time is effectively shortened, the identification method is simple and easy to implement, and the identification effect is better. It is intuitive and solves the technical problems that feature extraction and source identification in the existing voltage sag identification methods are separate operations, and the extracted features do not match the input and the identification time is long.

Description

technical field [0001] The invention relates to the technical field of voltage sag, and in particular to a method, device and equipment for identifying multiple disturbance sources of voltage sag based on PSO optimization width learning. Background technique [0002] Voltage sag refers to the phenomenon that the effective value of the supply voltage suddenly drops and then rises and recovers in a short period of time. At present, the identification method of voltage sag multiple interference sources is generally used to identify voltage sag, but the identification methods of voltage sag multiple interference sources mainly include: Two parts: feature extraction and source identification, source identification and feature extraction are separated, which increases the identification time to a certain extent. And feature extraction generally uses Fourier transform (FT), Wavelet Transform (WT), Hilbert-Huang Transform (HHT), S transform, etc. to extract the data. To a certain e...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/086G06N3/048G06N3/045G06F2218/12G06F2218/08G06F18/214Y02E60/00
Inventor 彭和平栾乐许中莫文雄王勇李晓马智远王海靖范伟男肖天为刘田
Owner GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
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