Adaptive neuro-fuzzy controller for static VAR compensator to damp out wind energy conversion system oscillation

Huazhang Huang, Chi Yung Chung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

28 Citations (Scopus)

Abstract

Wind shear and tower shadow produce a periodic pulse reduction in mechanical torque captured from wind energy resulting in wind energy conversion system (WECS) active power oscillations. In this study, an adaptive neuro-fuzzy controller for static VAR compensator, used in power networks integrated with WECS, is presented to address the torque oscillation problem. The proposed controller consists of a radial basis function neural network representing a third-order auto-regressive and moving average system model and performing the prediction, and a main controller with adaptive neuro-fuzzy inference system providing the damping signal. A modified two-area four-machine power network with WECS integration is applied to validate the proposed implementation, compared with conventional lead/lag compensation. Time-domain simulations prove that the proposed controller can provide a damping signal to improve the active power oscillation and system dynamic stability, influenced by torque oscillations under WECSs synchronised operating condition.

Original languageEnglish
Pages (from-to)200-207
Number of pages8
JournalIET Generation, Transmission and Distribution
Volume7
Issue number2
DOIs
Publication statusPublished - Feb 2013

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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