Power System Load Frequency Control: Classical and Adaptive Fuzzy Approaches
ISBN: 9781315166292
Platform/Publisher: Taylor & Francis / CRC Press
Digital rights: Users: Unlimited; Printing: Unlimited; Download: Unlimited
Subjects: Engineering & Technology; Electrical & Electronic Engineering; Power Engineering; Systems & Controls; Electronics;

This title presents a balanced blend between classical and intelligent load frequency control techniques, which is detrminant for continous supply of power loads. The classical control techniques introduced in this book include PID, pole placement, observer-based state feedback, static and dynamic output feedback controllers while the intelligent control techniques explained here are of adaptive fuzzy control types. This book will analyze and design different decentralized LF controllers in order to maintain the frequency deviations of each power area within the limits and keep the tie-line power flow between different power areas at the scheduled levels.


Hassan A. Yousef received the B.Sc. (honor) and M.Sc. degrees in Electrical Engineering from Alexandria University, Alexandria, Egypt in 1979 and 1983 respectively. He obtained the Ph.D. degree in Electrical and Computer Engineering from University of Pittsburgh, PA, USA in 1989. He spent 15 years in Alexandria University as assistant Professor, associate Professor and Professor. He joined Qatar University for 6 years as assistant Professor and then associate Professor. In Qatar University he held the position of acting head of Electrical and Computer Engineering Department. He was a visiting associate Professor in University of Florida, Gainesville in summer 1995. Now he is with the Department of Electrical and Computer Engineering, Sultan Qaboos University, Sultanate of Oman, Muscat. Dr. Yousef supervised 28 M.Sc. theses (completed) and 8 Ph.D. dissertations (completed). His publication records include 90 papers in refereed journals and international conferences in the area of control system, nonlinear control, adaptive fuzzy control and intelligent control applications to power systems and electric drives.

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