N-k Induced Cascading Contingency Screening

• Published in: IEEE transactions on power systems Vol. 30; no. 5; pp. 2824 - 2825
• Main Authors: Jia, Youwei, Meng, Ke, Xu, Zhao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-09-2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cascading failures; Entropy; Load modeling; N-k contingency screening; Power system faults; Power system protection; quantum inspired multi-objective evolutionary algorithm; random vector functional-link neural network; Risk management; Vectors
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2014.2361723

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.