Title :
Bayesian fault detection based on WAMS/PMU measurement system
Author :
Yagang Zhang ; Zengping Wang ; Jinfang Zhang
Author_Institution :
State Key Lab. of Alternate Electr. Power Syst. with Renewable Energy Sources, North China Electr. Power Univ., Baoding, China
Abstract :
The Bayesian fault detection based on WAMS/PMU measurement system will be clarified in this paper. Multivariate statistical analysis is an effective tool to finish the fault detection for electric power system. In Bayesian discriminant analysis as a sub branch, 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. A great number of simulation examples have confirmed that the results of Bayesian fault detection in wide area backup protection are accurate and reliable.
Keywords :
Bayes methods; fault diagnosis; phasor measurement; power system protection; probability; Bayesian discriminant analysis; Bayesian fault detection; WAMS-PMU measurement system; conditional probability; electric power system; multivariate statistical analysis; wide area backup protection; Bayesian methods; Electrical fault detection; Fault detection; Phasor measurement units; Power systems; Sociology; Statistics; Bayesian discriminant analysis; PMU; WAMS; fault detection; posterior probability;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6345199
