DocumentCode
108069
Title
N-k Induced Cascading Contingency Screening
Author
Youwei Jia ; Ke Meng ; Zhao Xu
Author_Institution
Dept. of Electr. Eng., Hong Kong Polytech. Univ., Hong Kong, China
Volume
30
Issue
5
fYear
2015
fDate
Sept. 2015
Firstpage
2824
Lastpage
2825
Abstract
This letter proposes a novel method for N-k induced cascading contingency screening based on random vector functional-link (RVFL) neural network and quantum inspired multi-objective evolutionary algorithm (QMEA). This method can conduct reliable and simultaneous screening for various N-k contingencies. The proposed method has been proved to be highly effective through a preliminary case study using the New England 39-bus system.
Keywords
evolutionary computation; neural nets; power engineering computing; transmission networks; vectors; N-k induced cascading contingency screening; New England 39-bus system; QMEA; RVFL neural network; quantum inspired multiobjective evolutionary algorithm; random vector functional-link neural network; Entropy; Load modeling; Power system faults; Power system protection; Risk management; Vectors; Cascading failures; N-k contingency screening; quantum inspired multi-objective evolutionary algorithm; random vector functional-link neural network;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2014.2361723
Filename
6923476
Link To Document