By Topic

The Research on Transient Stability Assessment Methods Based on Bayesian Network Classifier

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Jinling Lu ; Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Baoding ; Yongli Zhu ; Ren, Hui ; Zhongqiang Meng

Transient stability can be rapidly assessed using the artificial intelligence technology. In this paper, a fast transient stability assessment method based on Bayesian network classifier was proposed from the perspective of data mining. First, select the characteristic quantities which reflect the power system transient process rapidly as the attribute variables of the Bayesian network classifier, then determine the stable event's posterior probability using of the prior information and sample data which is produced massively by numerical simulation algorithm. When the disturbances occur, we can judge the power system is stabile or not by reasoning according to the corresponding attribute variables. Because any classifier has the probability of misclassification, the boosting algorithm of Bayesian network classifier is applied. Finally, we conduct a numerical simulation on New England 39-bus system to verify the effectiveness of the classifier.

Published in:

Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific

Date of Conference:

27-31 March 2009