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