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
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;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2014.2361723
