Probabilistic Eigenvalue Sensitivity Analysis and PSS Design in Multimachine Systems

C. Y. Chung, K. W. Wang, C. T. Tse, X. Y. Bian, A. K. David

Research output: Journal article publicationJournal articleAcademic researchpeer-review

92 Citations (Scopus)

Abstract

This paper presents an application of probabilistic theory to the selection of robust PSS locations and parameters. The aim is to enhance the damping of multiple electromechanical modes in a multimachine system over a large and prespecified set of operating conditions. Conventional eigenvalue analysis is extended to the probabilistic environment in which the statistical nature of eigenvalues corresponding to different operating conditions is described by their expectations and variances. Probabilistic sensitivity indices to facilitate "robust PSS" site selection and a probabilistic eigenvalue-based objective function for coordinated synthesis of PSS parameters are then proposed. The quasi-Newton technique of nonlinear programming is used to solve the objective function and its convergence properties are discussed and compared with the conventional steepest descent approach. The effectiveness of the proposed stabilizers, with a classical lead/lag structure, is demonstrated on an eight-machine system.

Original languageEnglish
Pages (from-to)1439-1445
Number of pages7
JournalIEEE Transactions on Power Systems
Volume18
Issue number4
DOIs
Publication statusPublished - Nov 2003

Keywords

  • Eigenvalue
  • Optimization
  • Power system stabilizer (PSS)
  • Probabilistic theory
  • Sensitivity

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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