Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Electric power big data visual neural network data mining technology-based electric power failure prediction method

A data mining and neural network technology, applied in biological neural network model, prediction, data processing application, etc., can solve the problems of low utilization efficiency of electric power big data, difficulty in predicting electric power failure, etc. Effect

Inactive Publication Date: 2018-05-04
STATE GRID ZHEJIANG ELECTRIC POWER +2
View PDF6 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to construct a power fault prediction method based on the visualization BP neural network data mining technology of electric power big data, so as to solve the problems of low utilization efficiency of electric power big data and difficulty in power fault prediction

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
  • Electric power big data visual neural network data mining technology-based electric power failure prediction method
  • Electric power big data visual neural network data mining technology-based electric power failure prediction method
  • Electric power big data visual neural network data mining technology-based electric power failure prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] Reference attached figure 1 , figure 2 , image 3 :

[0025] In order to make the discussion of the present invention clearer, the data screening and correlation analysis of the present invention are combined figure 1 And specific examples figure 2 , image 3 For further explanation, it should be noted that the specific examples described here are only used to explain the present invention and do not limit the present invention.

[0026] figure 1 In the data mining preprocessing and visualization processing module 3, the power big data 1 and the past fault time and type 2, such as line fault, circuit breaker fault, and transformer fault are numbered 1, 2, and 3 respectively. , Check the time of occurrence of this type of failure in the past, and conduct a data correlation test during a period of time from near to far in the time of the failure, set the significance level of correlation to 0.05, and obtain a failure number 1 with a time point exceeding 0.05. There are two...

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 an electric power big data visual neural network data mining technology-based electric power failure prediction method. The method comprises an electric power big database, a data mining preprocessing and visual processing module, a visual BP neural network data mining module and a result output module. According to the method, failure prediction is realized via a graphicalneural network data mining technology, so that the electric power big data using difficulty is reduced and the using efficiency is improved.

Description

Technical field [0001] The invention relates to a power failure prediction method based on power big data, in particular to a power failure prediction method based on the power big data visualization BP neural network data mining technology. Background technique [0002] In the process of power generation, transmission and distribution, a large amount of data will be generated and become power big data. These data contain various information of the power system and are very important for power system operation, dispatch, maintenance, fault diagnosis, and prediction. At present, the collection, analysis, and use of big power data are very limited, most of which are in the stage of manual processing or analysis and processing with simple software, which consumes a lot of manpower and material resources, is cumbersome to use, is very inefficient, and has little effect. At the same time, the damage caused by power failure is huge, and the power failure prediction technology is very i...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/02
CPCG06N3/02G06Q10/04G06Q50/06
Inventor 洪建光孔晓昀陈立跃汪自翔上官琳琳刘周斌张彩友黄海潮王志强刘鸿宁
Owner STATE GRID ZHEJIANG ELECTRIC POWER
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com