
Bayes-Based Fault Discrimination in Wide Area Backup Protection
Author(s) -
Z. Wang,
J. Zhang,
Y. Zhang
Publication year - 2012
Publication title -
advances in electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 23
eISSN - 1844-7600
pISSN - 1582-7445
DOI - 10.4316/aece.2012.01015
Subject(s) - backup , bayes' theorem , computer science , fault (geology) , reliability engineering , computer security , artificial intelligence , bayesian probability , database , engineering , geology , seismology
Multivariate statistical analysis is an effective tool to finish the fault location for electric power system. In Bayesian discriminant analysis as a subbranch, by the research of several populations, one can calculate the conditional probability that some samples belong to these populations, and compare the corresponding probability. The sample will be classified as population with maximum probability. In this paper, based on Bayesian discriminant analysis principle, a great number of simulation examples have confirmed that the results of Bayesian fault discriminant in wide area backup protection are accurate and reliable