Unlock instant, AI-driven research and patent intelligence for your innovation.

Voltage sag disturbance source positioning method fusing attention mechanism and deep learning

A technology for locating disturbance sources and voltage sags, applied in fault locations and other directions, can solve problems such as inability to locate voltage sag sources and low positioning accuracy, achieve strong anti-background noise interference and robustness, and improve accuracy , to avoid the effects of the feature extraction process

Pending Publication Date: 2021-04-20
XIAN UNIV OF TECH
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to provide a voltage sag disturbance source location method that integrates the attention mechanism and deep learning, which solves the problem of low location accuracy in the existing location method, and it is impossible to start and switch the transformer by the motor Disadvantages of precisely locating the source of the voltage sag caused by

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Voltage sag disturbance source positioning method fusing attention mechanism and deep learning
  • Voltage sag disturbance source positioning method fusing attention mechanism and deep learning
  • Voltage sag disturbance source positioning method fusing attention mechanism and deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0083] The voltage sag disturbance source location method based on the attention mechanism and the independent cyclic neural network deep learning fusion model is implemented according to the following steps:

[0084] Step 1, for the attached figure 2 The shown power system network IEEE39 node system to be tested has 34 lines in total, so the branches in the network are numbered 1-34 in sequence. In this embodiment, Matlab simulation software is used, and when various voltage sags caused by motor start-up, transformer switching, and short-circuit faults (including single-phase short-circuit faults, two-phase short-circuit faults, and three-phase short-circuit faults) occur in each branch, Obtain monitoring data at four monitoring points 3, 8, 24, and 38. The following principles should be followed in the process of data collection: a. The collected data must include various voltages caused by motor start-up, transformer switching, and short-circuit faults (including single-p...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a voltage sag disturbance source positioning method fusing an attention mechanism and deep learning. Characteristic information corresponding to voltage sag caused by motor starting, transformer switching and short-circuit faults (including single-phase short-circuit faults, two-phase short-circuit faults and three-phase short-circuit faults) can be directly and autonomously learned from original monitoring data, so that the integrity of voltage sag information can be ensured to the greatest extent; the tedious manual feature extraction process is avoided, and the positioning accuracy of the voltage sag disturbance source is improved.

Description

technical field [0001] The invention belongs to the technical field of power quality analysis and detection methods, and relates to a method for locating voltage sag disturbance sources that integrates attention mechanism and deep learning. Background technique [0002] As more and more sensitive loads are connected to the power grid, voltage sag has become one of the most prominent power quality problems. Voltage sag will not only bring serious economic losses but also may cause certain social impacts. Therefore, accurately locating the source of voltage sag disturbance is an important means and premise basis for dividing responsibility for events and taking effective countermeasures, and has important theoretical value and practical significance. [0003] At present, a research on the location of voltage sag disturbance sources mainly adopts a method based on physical models, that is, by establishing a mathematical model, analyzing the voltage, current, and power of volta...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G01R31/08
Inventor 邓亚平贾颢邱晓东王璐同向前林邵杰郑定坤张楠张亮殷珩
Owner XIAN UNIV OF TECH