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Title: Intelligent optimal control of excitation and turbine systems in power networks
Author (s): Venayagamoorthy, Ganesh K.
Harley, R.G.
Department/Lab Affiliations: Electrical and Computer Engineering
Real-Time Power and Intelligent Systems Laboratory
Keywords: Adaptive Critic Designs
Approximate Dynamic Programming
Excitation Control
Neural Networks
PI controllers
Reinforcement Learning
Turbine Control
adaptive control
distribution networks
excitation systems
intelligent control
intelligent optimal control
neurocontrollers
optimal control
optimal neurocontrol approaches
power grid highlights
power grids
power networks
power system control
power system excitation control
power system stability
real-time laboratory experimental studies
system stabilization
transmission networks
turbine systems
turbines
voltage control
Issue Date: 2006
Publisher: Institute of Electrical and Electronics Engineers
Citation: Venayagamoorthy, G.K.; Harley, R.G. "Intelligent optimal control of excitation and turbine systems in power networks" IEEE Power Engineering Society General Meeting, 2006. 18-22 June 2006 Pages: 8 pp.
Abstract: The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of excitation and turbine systems. The crucial factors affecting the modern power systems today is voltage control and system stabilization during small and large disturbances. Simulation studies and real-time laboratory experimental studies carried out are described and the results show the successful control of the power system excitation and turbine systems with adaptive and optimal neurocontrol approaches. Performances of the neurocontrollers are compared with the conventional PI controllers for damping under different operating conditions for small and large disturbances.
Type: Article - Conference proceedings
text
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titleIntelligent optimal control of excitation and turbine systems in power networks
contributor.authorVenayagamoorthy, Ganesh K.
contributor.authorHarley, R.G.
contributor.deptlabElectrical and Computer Engineering
contributor.deptlabReal-Time Power and Intelligent Systems Laboratory
subjectAdaptive Critic Designs
subjectApproximate Dynamic Programming
subjectExcitation Control
subjectNeural Networks
subjectPI controllers
subjectReinforcement Learning
subjectTurbine Control
subjectadaptive control
subjectdistribution networks
subjectexcitation systems
subjectintelligent control
subjectintelligent optimal control
subjectneurocontrollers
subjectoptimal control
subjectoptimal neurocontrol approaches
subjectpower grid highlights
subjectpower grids
subjectpower networks
subjectpower system control
subjectpower system excitation control
subjectpower system stability
subjectreal-time laboratory experimental studies
subjectsystem stabilization
subjecttransmission networks
subjectturbine systems
subjectturbines
subjectvoltage control
date.issued2006
date.submitted2007
publisherInstitute of Electrical and Electronics Engineers
identifier.citationVenayagamoorthy, G.K.; Harley, R.G. "Intelligent optimal control of excitation and turbine systems in power networks" IEEE Power Engineering Society General Meeting, 2006. 18-22 June 2006 Pages: 8 pp.
identifier.pub.URI
http://ieeexplore.ieee.org/iel5/11204/36065/01709491.pdf?arnumber=170949
description.abstractThe increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of excitation and turbine systems. The crucial factors affecting the modern power systems today is voltage control and system stabilization during small and large disturbances. Simulation studies and real-time laboratory experimental studies carried out are described and the results show the successful control of the power system excitation and turbine systems with adaptive and optimal neurocontrol approaches. Performances of the neurocontrollers are compared with the conventional PI controllers for damping under different operating conditions for small and large disturbances.
typeArticle - Conference proceedings
type.DCMITypetext
type.statusFinal version
rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
rights.URI
http://www.ieee.org/web/publications/rights/policies.html
date.accessioned2007-04-05T14:28:01Z
date.available2007-04-05T14:28:00Z
identifier.persist.URI
http://scholarsmine.mst.edu/post_prints/01709491_09007dcc8030db4a.html
Full Text
01709491_09007dcc8030db4f.pdf