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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 | |
| Copyright Notice: | This 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. FULL COPYRIGHT INFORMATION: | |
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| title | Intelligent optimal control of excitation and turbine systems in power networks | |
| contributor.author | Venayagamoorthy, Ganesh K. | |
| contributor.author | Harley, R.G. | |
| contributor.deptlab | Electrical and Computer Engineering | |
| contributor.deptlab | Real-Time Power and Intelligent Systems Laboratory | |
| subject | Adaptive Critic Designs | |
| subject | Approximate Dynamic Programming | |
| subject | Excitation Control | |
| subject | Neural Networks | |
| subject | PI controllers | |
| subject | Reinforcement Learning | |
| subject | Turbine Control | |
| subject | adaptive control | |
| subject | distribution networks | |
| subject | excitation systems | |
| subject | intelligent control | |
| subject | intelligent optimal control | |
| subject | neurocontrollers | |
| subject | optimal control | |
| subject | optimal neurocontrol approaches | |
| subject | power grid highlights | |
| subject | power grids | |
| subject | power networks | |
| subject | power system control | |
| subject | power system excitation control | |
| subject | power system stability | |
| subject | real-time laboratory experimental studies | |
| subject | system stabilization | |
| subject | transmission networks | |
| subject | turbine systems | |
| subject | turbines | |
| subject | voltage control | |
| date.issued | 2006 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.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. | |
| identifier.pub.URI | ||
| description.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 | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This 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 | ||
| date.accessioned | 2007-04-05T14:28:01Z | |
| date.available | 2007-04-05T14:28:00Z | |
| identifier.persist.URI | ||
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