Decentralized optimal neuro-controllers for generation and transmission devices in an electric power network

Jung Wook Park, Ronald G. Harley, Ganesh K. Venayagamoorthy

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

In this paper, the dual heuristic programming (DHP) optimization algorithm is applied for the design of two LOCAL nonlinear optimal neuro-controllers on a practical multi-machine power system. One neuro-controller is designed to replace the conventional linear controllers, which are the automatic voltage regulator (AYR) and speed-governor (GOV), for a synchronous generator. The other is a new external neuro-controller for the series capacitive reactance compensator (SCRC), flexible ac transmission systems (FACTS) device. The PSCAD/EMTDC® simulation results show that interactions of two DHP neuro-controllers with different control objectives improve the system performance more effectively compared to when each one operates without the presence of the other one.

Original languageEnglish
Pages (from-to)37-46
Number of pages10
JournalEngineering Applications of Artificial Intelligence
Volume18
Issue number1
DOIs
Publication statusPublished - 2005 Feb 1

Fingerprint

Heuristic programming
Controllers
Voltage regulators
Governors
Synchronous generators

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

Cite this

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Decentralized optimal neuro-controllers for generation and transmission devices in an electric power network. / Park, Jung Wook; Harley, Ronald G.; Venayagamoorthy, Ganesh K.

In: Engineering Applications of Artificial Intelligence, Vol. 18, No. 1, 01.02.2005, p. 37-46.

Research output: Contribution to journalArticle

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