scholarly journals Application of EOS-ELM With Binary Jaya-Based Feature Selection to Real-Time Transient Stability Assessment Using PMU Data

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 23092-23101 ◽  
Author(s):  
Yang Li ◽  
Zhen Yang
Keyword(s):  
Feature Selection ◽  
Real Time ◽  
Transient Stability ◽  
Stability Assessment

Application of Bayesian Learning Mechanism in Power System Transient Stability Assessment

2010 ◽  
Vol 108-111 ◽  
pp. 765-770
Author(s):  
Lin Niu ◽  
Jian Guo Zhao ◽  
Ke Jun Li ◽  
Zhen Yu Zhou
Keyword(s):  
Machine Learning ◽  
Power System ◽  
Real Time ◽  
Bayesian Learning ◽  
Transient Stability ◽  
Decision Function ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Svm Classifier ◽  
Stability Assessment

One of the most challenging problems in real-time operation of power system is the prediction of transient stability. Fast and accurate techniques are imperative to achieve on-line transient stability assessment (TSA). This problem has been approached by various machine learning algorithms, however they find a class decision estimate rather than a probabilistic confidence of the class distribution. To counter the shortcoming of common machine learning methods, a novel machine learning technique, i.e. ‘relevance vector machine’ (RVM), for TSA is presented in this paper. RVM is based on a probabilistic Bayesian learning framework, and as a feature it can yield a decision function that depends on only a very fewer number of so-called relevance vectors. The proposed method is tested on New England power system, and compared with a state-of-the-art ‘support vector machine’ (SVM) classifier. The classification performance is evaluated using false discriminate rate (FDR). It is demonstrated that the RVM classifier can yield a decision function that is much sparser than the SVM classifier while providing higher classification accuracy. Consequently, the RVM classifier greatly reduces the computational complexity, making it more suitable for real-time implementation.

scholarly journals Real-time transient stability assessment in power system based on improved SVM

2018 ◽  
Vol 7 (1) ◽  
pp. 26-37 ◽  
Author(s):  
Wei HU ◽  
Zongxiang LU ◽  
Shuang WU ◽  
Weiling ZHANG ◽  
Yu DONG ◽  
...  
Keyword(s):  
Power System ◽  
Real Time ◽  
Transient Stability ◽  
Stability Assessment
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