Nonlinear Power System Excitation Control Using Adaptive Wavelet Networks

H. Yousef, H. M. Soliman and M. H. Albadi

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

A wavelet network-based nonlinear excitation control is designed to enhance the transient stability of a power system. The power system model used to improve the transient stability via excitation control can be written in the canonical form. The resulting excitation control signal that achieves a prescribed tracking performance is shown to include unknown nonlinear terms. A wavelet network is constructed to generate an approximation of these nonlinear terms and hence facilitate the design of the nonlinear excitation controller. Based on the wavelet network approximation, suitable adaptive control and appropriate parameter update algorithm are developed to force the nonlinear uncertain power system to track a prescribed trajectory with desired dynamic performance. It is shown that the proposed controller achieves ultimately bounded tracking error and boundedness of the closed loop signals. A single machine infinite bus system with uncertain fault location is presented to illustrate the proposed design procedure and exhibit its performance. The performance of the proposed excitation controller is compared with the classical IEEE-type ST1A static exciter equipped with a power system stabilizer.

Original languageEnglish
Pages (from-to)302-311
Number of pages10
JournalNeurocomputing
Volume230
DOIs
Publication statusPublished - 2017

Keywords

  • Nonlinear excitation
  • Power system
  • Wavelet networks

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cognitive Neuroscience
  • Computer Science Applications

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