Probabilistic Reliability Evaluation including Adequacy and Dynamic Security Assessment

Yingying Wang, Vijay Vittal, Mojdeh Abdi-Khorsand, Chanan Singh

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


The growing penetration of variable renewable sources and the competitive power system environment make the application of probabilistic reliability techniques all the more important. Although probabilistic methods have been widely used in resource adequacy assessment, using probabilistic methodologies for reliability evaluation including system dynamic security need to be investigated. This paper proposes a probabilistic methodology for integrated reliability evaluation considering resource adequacy and dynamic security assessment in a unified framework. Sequential Monte Carlo simulation (SMCS) is chosen because of its ability to consider time-varying sequential characteristics. By using an optimization model, which minimizes load curtailment for adequacy assessment, and representing stability preserving protection systems in security assessment, the proposed approach gives quantitative integrated reliability evaluation results. In addition, two acceleration methods are introduced to improve computational efficiency. The proposed approach is demonstrated on a synthetic test system and the results illustrate the efficacy of an integrated reliability evaluation approach.

Original languageEnglish (US)
Article number8742636
Pages (from-to)551-559
Number of pages9
JournalIEEE Transactions on Power Systems
Issue number1
StatePublished - Jan 2020


  • Dynamic security assessment
  • Monte-Carlo simulation
  • reliability
  • renewable integrated grid

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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