Probabilistic small signal analysis using Monte Carlo simulation

Zhao Xu, Z. Y. Dong, P. Zhang

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

54 Citations (Scopus)


This paper presents a Monte Carlo approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. The uncertainties considered include both generation and demand in power systems, though others, such as parameter changes of network components, can be added as well. Probabilistic models of these uncertainties are constructed considering their characteristics. Subsequently, probabilistic small signal stability assessment of the power system is carried out based on eigenvalue analysis via Monte Carlo Simulation. The proposed method is tested by analysing the eigenvalues of two benchmark systems, where stable, unstable and oscillation modes are identified in the probabilistic context. In addition, local and inter-area modes of electro-mechanical oscillation are classified. Relevant discussion of stability enhancement using the proposed approach has been presented as well. The proposed method aims at providing a comprehensive characterization of system stability which can be very helpful in applications, such as system operation and expansion planning in the deregulation with many uncertainties.
Original languageEnglish
Title of host publication2005 IEEE Power Engineering Society General Meeting
Number of pages7
Publication statusPublished - 31 Oct 2005
Externally publishedYes
Event2005 IEEE Power Engineering Society General Meeting - San Francisco, CA, United States
Duration: 12 Jun 200516 Jun 2005


Conference2005 IEEE Power Engineering Society General Meeting
Country/TerritoryUnited States
CitySan Francisco, CA


  • Eigenvalue
  • Eigenvector
  • Monte Carlo simulation
  • Participation factor
  • Probabilistic methods
  • Small signal stability

ASJC Scopus subject areas

  • General Engineering


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