Power distribution network fault recovery method based on self-learning mechanism

A technology of distribution network failure and recovery method, applied in the direction of automatic disconnection of emergency protection devices, electrical components, circuit devices, etc., can solve the problems of slow speed and poor solution performance.

Active Publication Date: 2020-04-28
STATE GRID HENAN ELECTRIC POWER COMPANY ZHENGZHOU POWER SUPPLY +2
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is: to overcome the deficiencies of the existing technology, to provide a method that can solve the defects of slow speed and poor performance of the traditio

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
  • Power distribution network fault recovery method based on self-learning mechanism
  • Power distribution network fault recovery method based on self-learning mechanism
  • Power distribution network fault recovery method based on self-learning mechanism

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] Attached below figure 1 , figure 2 , image 3 The present invention is further explained and described with specific embodiment:

[0041] A distribution network fault recovery method based on a self-learning mechanism, comprising the following steps:

[0042] Step 1: Construct a self-learning database; when the distribution network is in normal operation, reasonably formulate the expected accident set according to the risk assessment results, and carry out the expected accident simulation on high-risk equipment and locations in sequence according to the order of risk from high to low, so as to build a network based on Anticipated accident simulation and self-learning database of historical fault handling schemes, so that power supply schemes for similar faults can be directly used after a fault;

[0043] Step 2: Evaluation and matching of similar fault states; after the fault, extract the characteristics of the current network fault, and sequentially calculate the n...

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 power distribution network fault recovery method based on a self-learning mechanism. According to the method, anticipated accident simulation is performed according to a riskevaluation result during the normal operation of a power grid; a self-learning database based on an accident plan and a historical fault recovery scheme is built; after a faults occur, fault featuresare extracted, the similarities of the current fault and faults stored in the database are calculated, and are sorted according to the sequence from high similarities to low similarities; and a powersupply recovery task is quickly and reliably realized by utilizing a power supply recovery scheme of a fault which is similar to the current fault and is obtained through matching. According to the method of the invention, a traditional complex and time-consuming online optimization problem is converted into the similarity evaluation problem of finite fault states; and therefore, a real-time calculation amount is greatly reduced while the quality of the fault recovery scheme is ensured, power supply recovery decision speed and scheme performance are improved, and a power supply recovery system is upgraded into an intelligent control system with self-learning, self-perfecting and evolutionary capabilities.

Description

technical field [0001] The invention relates to a distribution network fault recovery method based on a self-learning mechanism, which belongs to the field of power system automation and distribution network fault recovery. Background technique [0002] The distribution network in the power system undertakes the important task of distributing electric energy to thousands of households, which directly affects the power supply reliability and power quality of power users. With the development of social economy and the continuous improvement of living standards, the reliability of distribution network power supply will be improved. As the core function of self-healing control of smart distribution network, power supply restoration is of great significance to improve the reliability of power grid power supply. [0003] The restoration of power supply in the distribution network needs to take into account factors such as power loss load, switching times, load balance, voltage qua...

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): H02H7/26H02H3/06
CPCH02H7/262H02H3/066Y04S10/52
Inventor 鲍薇辛忠良燕跃豪孔汉杰赵乔董文娜王增平
Owner STATE GRID HENAN ELECTRIC POWER COMPANY ZHENGZHOU POWER SUPPLY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products