Einladung zum Vortrag im Kolloquium Technische Kybernetik
Power System Stability Enhancement
through Adaptive and Intelligent Control
Prof. Om P. Malik
Department of Electrical and Computer Engineering
University of Calgary
Calgary, Canada
Zeit: Dienstag · 28. 11. 2006 · 16:00 Uhr
Ort: IST-Seminarraum 3.241 · Pfaffenwaldring 9 · Campus Stuttgart-Vaihingen
Abstract
Conventional and linear optimal controllers are based on the deterministic control theory. They are designed using a linear system model obtained for a particular operating condition. The non-linearities, wide range of operating conditions and non-deterministic properties of most large systems, such as power systems, present problems to the conventional controllers.
Adaptive control theory offers a technique for the design of a controller that can mitigate the above problems. Consider a non-linear system subject to a wide range of operating conditions, and random and unpredictable disturbances. To compute appropriate control for such a system as operating conditions vary, the system parameters are tracked by a mathematical model that describes the actual system. For the model to track the system dynamics, its parameters are time varying and are updated regularly using a parameter estimation technique, called the identifier.
The identified parameters of the system model are used in the controller to compute the appropriate feedback control signal. This procedure is carried out recursively on-line during each sampling interval. The adaptive controller thus consists of an identifier to compute the updated parameters of a discrete model of the system that tracks the system operating conditions, and a controller that computes the appropriate control based on the estimated model parameters.
Developments in digital technology have made it feasible to develop and implement improved controllers based on modern more sophisticated techniques. The strength of this approach will be illustrated using power system stabilizer as an application example. Use of neural networks and fuzzy logic in the design of such controllers will be illustrated and the performance of such controllers by both simulation studies and real-time tests on a physical model of a power system will also be discussed.
Biographical Information
Professor Om P. Malik has done pioneering work in the development of adaptive and artificial intelligence based controllers for application in electric power systems over the past thirty years. After extensive testing in the laboratory and in actual power systems, these controllers are now employed on large generating units.
Professor Malik has also done extensive work in the area of power system protection, particularly digital and artificial intelligence based protection schemes. He has published over 600 papers including almost 300 papers in international Journals.
Professor Malik graduated in 1952 from Delhi Polytechnic, India. After working for nine years in electric utilities in India, he returned to academia and obtained a Master's Degree from Roorkee University, India in 1962, a Ph.D. from London University and a DIC from the Imperial College, London in 1965.
He was teaching and doing research in Canada from 1966 to 1997 and continues to do research as Professor Emeritus at the University of Calgary, Canada.
Om Malik has been doing volunteer work for IEEE for over 35 years at the Section, Council, Region and IEEE corporate level for over 35 years. He is also actively involved in the IEEE Power Engineering Society.
Professor Malik is a Fellow of the Engineering Institute of Canada, Canadian Academy of Engineering, Institution of Electrical Engineers, World Innovation Foundation and a Life Fellow of IEEE. He has received many awards from IEEE, EIC and APPEGA and the University of Calgary. He is a member of the Association of Professional Engineers, Geologists and Geophysicists of Alberta and Professional Engineers Ontario. Professor Malik is also actively involved in IFAC and is currently Chair of the IFAC Technical Committee on Power Plants and Power Systems Control.
|
Universität Stuttgart