Adaptive Neural Network Identifiers for Effective Control of Turbogenerators in a Multimachine Power System

G. K. Venayagamoorthy; R. G. Harley; D. C. Wunsch

doi:10.1109/PESW.2001.917265

Adaptive Neural Network Identifiers for Effective Control of Turbogenerators in a Multimachine Power System

G. K. Venayagamoorthy
, R. G. Harley
, D. C. Wunsch

University of KwaZulu-Natal
Georgia Institute of Technology
Missouri University of Science and Technology

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper provides a novel method for nonlinear identification of multiple turbogenerators in a five-machine 12-bus power system using continually online trained (COT) artificial neural networks (ANNs). Each turbogenerator in the power system is equipped with all adaptive ANN identifier, which is able to identify/model its particular turbogenerator and rest of the network to which it is connected from moment to moment, based on only local measurements. Each adaptive ANN turbogenerator can be used in the design of a nonlinear controller for each turbogenerator in a multimachine power system. Simulation results for the adaptive ANN identifiers are presented

Original language	American English
Pages	1294-1299
Number of pages	6
DOIs	https://doi.org/10.1109/PESW.2001.917265
State	Published - Aug 1 2002
Externally published	Yes
Event	2001 IEEE Power Engineering Society Winter Meeting - Columbus, OH, United States Duration: Jan 28 2001 → Feb 1 2001

Conference

Conference	2001 IEEE Power Engineering Society Winter Meeting
Country/Territory	United States
City	Columbus, OH
Period	1/28/01 → 2/1/01

ASJC Scopus Subject Areas

Electrical and Electronic Engineering

Keywords

Adaptive identification
Artificial neural networks
Control
Multimachine power system

Disciplines

Electrical and Computer Engineering

Access to Document

10.1109/PESW.2001.917265License: Unspecified

Adaptive Neural Network Identifiers for Effective Control of TurbFinal published version, 731 KBLicense: Unspecified

Cite this

@conference{19e04afccb7546d9aeeab8b08cd83b59,

title = "Adaptive Neural Network Identifiers for Effective Control of Turbogenerators in a Multimachine Power System",

abstract = " This paper provides a novel method for nonlinear identification of multiple turbogenerators in a five-machine 12-bus power system using continually online trained (COT) artificial neural networks (ANNs). Each turbogenerator in the power system is equipped with all adaptive ANN identifier, which is able to identify/model its particular turbogenerator and rest of the network to which it is connected from moment to moment, based on only local measurements. Each adaptive ANN turbogenerator can be used in the design of a nonlinear controller for each turbogenerator in a multimachine power system. Simulation results for the adaptive ANN identifiers are presented",

keywords = "Adaptive identification, Artificial neural networks, Control, Multimachine power system",

author = "Venayagamoorthy, \{G. K.\} and Harley, \{R. G.\} and Wunsch, \{D. C.\}",

year = "2002",

month = aug,

day = "1",

doi = "10.1109/PESW.2001.917265",

language = "American English",

pages = "1294--1299",

note = "2001 IEEE Power Engineering Society Winter Meeting ; Conference date: 28-01-2001 Through 01-02-2001",

}

TY - CONF

T1 - Adaptive Neural Network Identifiers for Effective Control of Turbogenerators in a Multimachine Power System

AU - Venayagamoorthy, G. K.

AU - Harley, R. G.

AU - Wunsch, D. C.

PY - 2002/8/1

Y1 - 2002/8/1

N2 - This paper provides a novel method for nonlinear identification of multiple turbogenerators in a five-machine 12-bus power system using continually online trained (COT) artificial neural networks (ANNs). Each turbogenerator in the power system is equipped with all adaptive ANN identifier, which is able to identify/model its particular turbogenerator and rest of the network to which it is connected from moment to moment, based on only local measurements. Each adaptive ANN turbogenerator can be used in the design of a nonlinear controller for each turbogenerator in a multimachine power system. Simulation results for the adaptive ANN identifiers are presented

AB - This paper provides a novel method for nonlinear identification of multiple turbogenerators in a five-machine 12-bus power system using continually online trained (COT) artificial neural networks (ANNs). Each turbogenerator in the power system is equipped with all adaptive ANN identifier, which is able to identify/model its particular turbogenerator and rest of the network to which it is connected from moment to moment, based on only local measurements. Each adaptive ANN turbogenerator can be used in the design of a nonlinear controller for each turbogenerator in a multimachine power system. Simulation results for the adaptive ANN identifiers are presented

KW - Adaptive identification

KW - Artificial neural networks

KW - Control

KW - Multimachine power system

UR - https://www.scopus.com/pages/publications/0038646616

UR - https://www.scopus.com/pages/publications/0038646616#tab=citedBy

U2 - 10.1109/PESW.2001.917265

DO - 10.1109/PESW.2001.917265

M3 - Paper

SP - 1294

EP - 1299

T2 - 2001 IEEE Power Engineering Society Winter Meeting

Y2 - 28 January 2001 through 1 February 2001

ER -

Adaptive Neural Network Identifiers for Effective Control of Turbogenerators in a Multimachine Power System

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

Other files and links

Fingerprint

Cite this