Indirect adaptive neurocontrol scheme for a static compensator connected to a power system

Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley, Jung Wook Park, Mariesa L. Crow

Research output: Contribution to journalConference article

Abstract

An indirect adaptive neurocontrol scheme for a Static Compensator connected to a power system using two Artificial Neural Networks (ANNs) is presented in this paper. The ANNs are trained online and there is no need for offline data. The neurocontroller has a better performance in adaptively controlling the Static Compensator and damping the system transients, compared to conventional controllers. Preliminary results are provided to show the performance of the neurocontroller for large disturbances.

Original languageEnglish
Pages (from-to)623-628
Number of pages6
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume36
Issue number20
DOIs
Publication statusPublished - 2003 Jan 1
Event5th IFAC Symposium on Power Plants and Power Systems Control 2003 - Seoul, Korea, Republic of
Duration: 2003 Sep 152003 Sep 19

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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