Risk-Based Power System Security Analysis Considering Cascading Outages

Youwei Jia, Zhao Xu, Loi Lei Lai, Kit Po Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

73 Citations (Scopus)


Successful development of smart grid demands strengthened system security and reliability, which requires effective security analysis in conducting system operation and expansion planning. Classical N - 1 criterion has been widely used to examine every creditable contingency through detailed computations in the past. The adequacy of such approach becomes doubtful in many recent blackouts where cascading outages are usually involved. This may be attributed to the increased complexities and nonlinearities involved in operating conditions and network structures in context of smart grid development. To address security threats, particularly from cascading outages, a new and efficient security analysis approach is proposed, which comprises cascading failure simulation module (CFSM) for postcontingency analysis and risk evaluation module (REM) based on a decorrelated neural network ensembles (DNNE) algorithm. This approach overcomes the drawbacks of high computational cost in classical N-k-induced cascading contingency analysis. Case studies on two different IEEE test systems and a practical transmission system - Polish 2383-bus system have been conducted to demonstrate the effectiveness of the proposed approach for risk evaluation of cascading contingency.
Original languageEnglish
Article number7327191
Pages (from-to)872-882
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Issue number2
Publication statusPublished - 1 Apr 2016


  • Cascading failures
  • contingency
  • data mining
  • N-k
  • security analysis
  • smart grids

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Risk-Based Power System Security Analysis Considering Cascading Outages'. Together they form a unique fingerprint.

Cite this