DocumentCode
2247225
Title
A fuzzy method for power system model reduction
Author
Wang, Shu-Chen ; Huang, Pei-Haw
Author_Institution
Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
Volume
2
fYear
2004
fDate
25-29 July 2004
Firstpage
891
Abstract
This paper studies the order reduction of power system dynamic models by fuzzy clustering. Based on the fuzzy c-means algorithm, a method is proposed for clustering the poles and the zeros of the original power system model into new clusters from which a reduced-order model can be obtained. Results from applying the method to a sample power system are demonstrated to show the validity of the proposed method.
Keywords
fuzzy set theory; pattern clustering; poles and zeros; power system control; reduced order systems; statistical analysis; fuzzy c-means algorithm; fuzzy clustering; order reduction; power system dynamic model reduction; reduced order model; Clustering algorithms; Clustering methods; Fuzzy systems; Partitioning algorithms; Poles and zeros; Power system analysis computing; Power system dynamics; Power system modeling; Power system stability; Reduced order systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
ISSN
1098-7584
Print_ISBN
0-7803-8353-2
Type
conf
DOI
10.1109/FUZZY.2004.1375524
Filename
1375524
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