DocumentCode :
3362753
Title :
Transient Stability Analysis of Large-Scale Power Systems Based on Reduce Feature
Author :
Sun, Shuangxue ; Li, Chan ; Zai, Xiwei ; Yang, Xiaoguang ; Liu, Yingtong ; Zhou, Xiaoxia ; Fan, Youping
Author_Institution :
Fac. of Electr. Eng., Univ. of Wuhan, Wuhan
fYear :
2009
fDate :
27-31 March 2009
Firstpage :
1
Lastpage :
4
Abstract :
This paper presents an effective data analysis approach for character data compression from bi-direction. At the first step of the algorithm, basing on the theory of component analysis, the paper adopt a principal component analysis approach to reduce the dimension of data horizontally, then after comparison of existing clustering algorithms, put forward an immune clustering algorithm based on similarity measurement of principle component core for vertical reduction by using related mechanism of clone selection as well as immune network self-stabilization in organism natural immune system for reference. Finally, a pattern discrimination model based on a cerebellar model articulation controller neural network was developed. Simulation experiments on the data from the process control field proved the effectiveness of this algorithm.
Keywords :
data compression; fault diagnosis; large-scale systems; learning (artificial intelligence); neural nets; pattern clustering; power system analysis computing; power system transient stability; principal component analysis; cerebellar model articulation controller neural network; character data compression; clustering algorithm; component analysis theory; data analysis approach; immune clustering algorithm; large-scale power systems; pattern discrimination model; principal component analysis; transient stability analysis; Bidirectional control; Clustering algorithms; Data analysis; Data compression; Large-scale systems; Power system analysis computing; Power system stability; Power system transients; Stability analysis; Transient analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2486-3
Electronic_ISBN :
978-1-4244-2487-0
Type :
conf
DOI :
10.1109/APPEEC.2009.4918943
Filename :
4918943
Link To Document :
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