N-k Induced Cascading Contingency Screening

Youwei Jia; Ke Meng; Zhao Xu

doi:10.1109/TPWRS.2014.2361723

N-k Induced Cascading Contingency Screening

Youwei Jia, Ke Meng, Zhao Xu

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

43 Citations (Scopus)

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.

Original language	English
Article number	6923476
Pages (from-to)	2824-2825
Number of pages	2
Journal	IEEE Transactions on Power Systems
Volume	30
Issue number	5
DOIs	https://doi.org/10.1109/TPWRS.2014.2361723
Publication status	Published - 1 Sept 2015

Keywords

Cascading failures
N-k contingency screening
quantum inspired multi-objective evolutionary algorithm
random vector functional-link neural network

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

More information

10.1109/TPWRS.2014.2361723

Cite this

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KW - quantum inspired multi-objective evolutionary algorithm

KW - random vector functional-link neural network

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DO - 10.1109/TPWRS.2014.2361723

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N-k Induced Cascading Contingency Screening

Abstract

Keywords

ASJC Scopus subject areas

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