Risk based identification of cascading chains based on generalized line outage distribution factors

Yuanyu Dai, Yusheng Xue, Guo Chen, Yan Xu, Zhao Xu, Z. Y. Dong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

In the past decades, many countries have suffered from serious blackouts which demonstrate catastrophic consequences caused by rare events in power systems. To address the emerged issues, the contingency screening and ranking should consider the risks of potential failures instead of the associated probabilities of following-up failures alone. However, it is computationally infeasible to evaluate all possible cascading failure sequences beforehand. Thus, fast risk assessment method should be developed to enhance computation efficiency while maintaining acceptable accuracy. In this paper, based on distribution factors and pre-contingency power flow conditions, a novel risk index is proposed to quickly assess the consequences of possible cascading failures. Then creditable cascading failure sequences can be determined and ranked according to the risk index. In addition, case studies on the IEEE-118 bus system show that the computational efficiency of the proposed cascading assessment method can be greatly enhanced with satisfactory accuracy, indicating a high potential of practical implementation.
Original languageEnglish
Title of host publicationProceedings - 2013 4th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2013
PublisherIEEE Computer Society
Pages553-556
Number of pages4
ISBN (Print)9781479927913
DOIs
Publication statusPublished - 1 Jan 2013
Event4th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2013 - Zhangjiajie, Hunan, China
Duration: 6 Nov 20137 Nov 2013

Conference

Conference4th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2013
Country/TerritoryChina
CityZhangjiajie, Hunan
Period6/11/137/11/13

Keywords

  • Cascading chain
  • Distribution factors
  • Risk

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

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