Coordination of PSSs and SVC damping controller to improve probabilistic small-signal stability of power system with wind farm integration

X. Y. Bian, Yan Geng, Kwok L. Lo, Yang Fu, Q. B. Zhou

Research output: Contribution to journalArticle

68 Citations (Scopus)
38 Downloads (Pure)

Abstract

A modified fruit fly optimization algorithm (MFOA) combined with a probabilistic approach are proposed in this paper to coordinate and optimize the parameters of power system stabilizers (PSSs) and static VAR compensator (SVC) damping controller for improving the probabilistic small-signal stability of power systems with large-scale wind generation, taking into consideration the stochastic uncertainty of system operating conditions. It is generally accepted that there is a threat to the stability of power system with penetration of wind farm. In addition, the stochastic fluctuations of wind generation make PSSs tuning more difficult. In this paper, PSSs and SVC damping controller are employed for suppressing local and inter-area low frequency oscillation. In order to eliminate the adverse effect between PSSs and SVC damping controller, the MFOA based on the probabilistic eigenvalue is applied to coordinate and optimize their parameters. The effectiveness of the proposed approach is verified on two test systems.

Original languageEnglish
Pages (from-to)2371-2382
Number of pages12
JournalIEEE Transactions on Power Systems
Volume31
Issue number3
Early online date7 Aug 2015
DOIs
Publication statusPublished - 1 May 2016

Keywords

  • modified fruit fly optimization algorithm (MFOA)
  • power system stabilizer (PSS)
  • probabilistic small-signal stability
  • static VAR compensator (SVC)

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