A Computationally Efficient Method to Design Probabilistically Robust Wide-Area PSSs for Damping Inter-Area Oscillations in Wind-Integrated Power Systems

Jingsen Zhou, Deping Ke, C. Y. Chung, Yuanzhang Sun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)

Abstract

This paper proposes an efficient method that tunes wide-area power system stabilizers (WPSSs) to have probabilistic robustness for damping inter-area electromechanical oscillations in power systems with incorporated random wind power. Specifically, the efficiency of this method benefits from unique consideration and deduction of the analytic forms of cumulative distribution functions (cdfs) of two types of random variables and their derivatives with respect to tunable parameters of the conventionally structured WPSSs, based on approximations of wind power probability density functions by Gaussian mixtures. These cdfs then compose the objective function of an optimization that can rapidly solve for optimal parameters of WPSSs by a sequential quadratic programming algorithm. The optimized WPSSs are probabilistically robust because they enhance the probability of two commonly desired control effects. Simulation studies on a modified IEEE 10-machine and 39-bus system validate the superior efficiency of the proposed tuning method and the excellent performance of the derived WPSSs.

Original languageEnglish
Article number8315048
Pages (from-to)5692-5703
Number of pages12
JournalIEEE Transactions on Power Systems
Volume33
Issue number5
DOIs
Publication statusPublished - Sept 2018
Externally publishedYes

Keywords

  • Gaussian mixture
  • mathematical programming
  • probability
  • robust
  • wide-area power system stabilizer

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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