A knowledge based decision support algorithm for power transmission system vulnerability impact reduction

Akdeniz E., Bağrıyanık M.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, vol.78, pp.436-444, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 78
  • Publication Date: 2016
  • Doi Number: 10.1016/j.ijepes.2015.11.041
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.436-444
  • Keywords: Power system vulnerability analysis, Non-operational vulnerability indices, Fuzzy inference system, Knowledge based decision support algorithm, NEURAL-NETWORK, SECURITY
  • Istanbul Technical University Affiliated: Yes


One of the main reasons for wide area blackouts is cascading failures due to critical contingencies. Since, several factors such as faults, misoperations, environmental effects and sabotage issues are involved; the analysis of such contingencies is a challenging process. Most available methods in literature deal mainly with a certain aspect of the problem. In this study, a more comprehensive methodology using operational and non-operational indices for power system vulnerability analysis is presented. The individual indices are defined for power system's operational performance, terrorist attack and adverse weather conditions where a fuzzy inference system is used to obtain a single Total Vulnerability Index for each transmission system line. Additionally, a knowledge based decision support algorithm is proposed for the use of TSO's defense activities in order to determine the weak points and counter measures like load shedding. The modeling approach is tested on IEEE reliability test network with imposed external constraints. (C) 2015 Elsevier Ltd. All rights reserved.