Paper Title:
Research of Bus Protection Based on Support Vector Machine with Parameter Optimization
  Abstract

Bus reliability is essential for maintaining the steady state of electrical network in power plants and power transformer stations. Researches on techniques and methods to achieve highly reliable and intelligent bus protection are very important. A new bus protection method based on parameter optimization of the support vector machine (SVM) is provided in this study. Various types of fault data were collected and used as samples for sorting comparison and analysis of different bus faults. Data were obtained by comparing the SVM method with the artificial neural network (ANN) method. The results suggest that the SVM model using RBF kernel can better distinguish among bus normal operation and different bus fault types than the ANN model, and meet the precision requirements for bus protection.

  Info
Periodical
Advanced Materials Research (Volumes 271-273)
Edited by
Junqiao Xiong
Pages
823-828
DOI
10.4028/www.scientific.net/AMR.271-273.823
Citation
H. Han, H. J. Wang, C. T. Huang, B. Long, "Research of Bus Protection Based on Support Vector Machine with Parameter Optimization", Advanced Materials Research, Vols. 271-273, pp. 823-828, 2011
Online since
July 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Lu Yang Jing, Dong Xiang Chen, Tai Yong Wang, Peng Wang
Chapter 4: Algorithms and Methods of Data and Signal Processing in Technique of Measurements and Fault Detection
Abstract:Oil tubing is one of the most used equipment in oil extraction operations. An effective diagnosis system for it can provide multifarious...
1405