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

Small sample relay protection reliability parameter estimation method based on SVM (Support Vector Machine)

A technology of parameter estimation and relay protection, applied in computing, data processing applications, instruments, etc., can solve the problems of short operation time of smart substations, lack of prior knowledge and statistical samples, etc.

Inactive Publication Date: 2015-08-12
STATE GRID CORP OF CHINA +3
View PDF3 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] The purpose of the present invention is to provide a small sample relay protection reliability parameter estimation method based on SVM in order to overcome the above-mentioned defects in the prior art, which can effectively overcome the problems caused by the short operation time of smart substations, prior knowledge and statistical samples. Extremely lacking problems are helpful for objective analysis and evaluation of protection system reliability

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
  • Small sample relay protection reliability parameter estimation method based on SVM (Support Vector Machine)
  • Small sample relay protection reliability parameter estimation method based on SVM (Support Vector Machine)
  • Small sample relay protection reliability parameter estimation method based on SVM (Support Vector Machine)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0066] Such as Figure 4 As shown, the small sample relay protection reliability parameter estimation method based on SVM includes the following steps:

[0067] S100. Using an empirical formula, calculate the empirical reliability of the original failure sample, and perform linearization processing;

[0068] S200, adopting the SVM algorithm, performing regression on the failure data, and predicting and generating new enlarged samples;

[0069] S300. Perform linear fitting on the original failure data, and use the obtained parameter estimation value as a new iteration initial value;

[0070] S400. Perform least squares fitting on the expanded new samples to obtain a final reliability parameter estimation result.

[0071] Insufficient sample size will cause or exacerbate multiple correlations between variables, which will seriously affect the accuracy and stability of the least squares algorithm [6] . In this paper, taking advantage of the outstanding advantages of the SVM a...

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 relates to a small sample relay protection reliability parameter estimation method based on a SVM (Support Vector Machine). The method comprises the following steps: 1, using an empirical formula to calculate the empirical reliability of an original failure sample and performing linear processing; 2, using a SVM algorithm to perform regression of failure data and performing prediction to generate a new enlarged sample; 3, performing linear fitting of the original failure data to obtain a parameter estimation value as a new iteration initial value; and 4, performing least square fitting of the enlarged new sample to obtain a final reliability parameter estimation result. Compared with the prior art, the method provided by the invention can effectively solve problems that priori knowledge and statistical samples are extremely in shortage as the operation time of an intelligent transformer station is short, and is beneficial for objective analysis and evaluation of reliability of a protection system.

Description

technical field [0001] The invention relates to a method for estimating reliability parameters of relay protection, in particular to a method for estimating reliability parameters of relay protection with small samples based on SVM. Background technique [0002] In smart substations, changes in sampling and tripping methods lead to great changes in the structure of protection devices [1]. In order to accurately evaluate the reliability of the protection system, it is necessary to obtain the reliability basic parameters of these new devices. At present, the least square estimation method is mostly used in the estimation of relay protection reliability parameters. For example, literature [2] uses least square estimation to obtain the survival function of incomplete censored data, and literature [3] uses least square method and average rank Method to estimate the distribution function of relay protection device life, literature [4] uses the least square method to estimate the ...

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): G06Q10/06G06Q50/06
Inventor 周泽昕何旭张沛超高翔姜宪国李仲青
Owner STATE GRID CORP OF CHINA
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