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Erscheint vorauss. 28. Mai 2026
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This book presents advanced Dynamic State Estimation (DSE) methodologies across three power system classes: quasi-steady power systems, synchronous-generator-based multi-machine systems and renewable energy microgrids. The work tackles unconventional measurements including time-delays, multi-rate measurements, event-triggered transmissions, outliers, and sensor saturations including complex factors. The nine-chapter structure progresses from fundamentals through specific applications to future research directions. * Explore state estimation in power systems and challenges in large, complex…mehr

Produktbeschreibung
This book presents advanced Dynamic State Estimation (DSE) methodologies across three power system classes: quasi-steady power systems, synchronous-generator-based multi-machine systems and renewable energy microgrids. The work tackles unconventional measurements including time-delays, multi-rate measurements, event-triggered transmissions, outliers, and sensor saturations including complex factors. The nine-chapter structure progresses from fundamentals through specific applications to future research directions. * Explore state estimation in power systems and challenges in large, complex grids with high renewable energy integration. * Provides step-by-step derivations of theoretical results and case studies based on widely used power system benchmarks. * Addresses two prominent research and technological aspects: soft computing for estimation and power electrical systems. * Considers practical issues such as online application and computational efficiency in the estimator design, * Reviews analysis techniques such as optimal estimation technique, completing the square method, stochastic analysis technique, and entropy theory This book is aimed at graduate students and researchers in electrical engineering, power systems, control systems, and signal processing.
Autorenporträt
Bogang Qu received the B.Eng. degree in electrical engineering and automation and the M.Eng. degree in electrical engineering from University of Shanghai for Science and Technology, Shanghai, China, in 2014 and 2017, respectively, and the Ph.D. degree in control science and engineering from Donghua University, Shanghai, China, in 2022. He is currently a Lecturer with the College of Automation Engineering, Shanghai University of Electric Power, Shanghai. From November 2021 to October 2022, he was a visiting Ph.D. Student with the Department of Computer Science, Brunel University London, Uxbridge, U.K. His current research interests include state estimation and information perception and their applications in smart grids. He is a very active reviewer for many international journals. Zidong Wang is Professor of Dynamical Systems and Computing at Brunel University London, London, U.K. He was born in 1966 in Yangzhou, Jiangsu, China. He received the BSc degree in Mathematics in 1986 from Suzhou University, Suzhou, the MSc degree in Applied Mathematics in 1990 and the PhD degree in Electrical and Computer Engineering in 1994, both from Nanjing University of Science and Technology, Nanjing. He was appointed as Lecturer in 1990 and Associate Professor in 1994 at Nanjing University of Science and Technology. From January 1997 to December 1998, he was an Alexander von Humboldt research fellow with the Control Engineering Laboratory, Ruhr-University Bochum, Germany. From January 1999 to February 2001, he was a Lecturer with the Department of Mathematics, University of Kaiserslautern, Germany. From March 2001 to July 2002, he was a University Senior Research Fellow with the School of Mathematical and Information Sciences, Coventry University, U.K. In August 2002, he joined the Department of Computer Science, Brunel University London, U.K., as a Lecturer, and was then promoted to a Reader in September 2003 and to a Chair Professor in July 2007. Professor Wang's research interests include dynamical systems, signal processing, bioinformatics, control theory and applications. He has published more than 700 papers in refereed international journals. He was awarded the Humboldt research fellowship in 1996 from Alexander von Humboldt Foundation, the JSPS Research Fellowship in 1998 from Japan Society for the Promotion of Science, and the William Mong Visiting Research Fellowship in 2002 from the University of Hong Kong. He was a recipient of the State Natural Science Award from the State Council of China in 2014 and the Outstanding Science and Technology Development Awards (once in 2005 and twice in 1997) from the National Education Committee of China. Professor Wang is currently serving or has served as the Editor-in-Chief for International Journal of Systems Science, the Editor-in-Chief for Neurocomputing, Executive Editor for Systems Science and Control Engineering, Subject Editor for Journal of The Franklin Institute, an Associate Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, IEEE Transactions on Systems, Man, and Cybernetics- Systems, Asian Journal of Control, Science China Information Sciences, IEEE/CAA Journal of Automatica Sinica, Control Theory and Technology, an Action Editor for Neural Networks, an Editorial Board Member for Information Fusion, IET Control Theory & Applications, Complexity, International Journal of Systems Science, Neurocomputing, International Journal of General Systems, Studies in Autonomic, Data-driven and Industrial Computing, and a member of the Conference Editorial Board for the IEEE Control Systems Society. He served as an Associate Editor for IEEE Transactions on Neural Networks, IEEE Transactions on Systems, Man, and Cybernetics - Part C, IEEE Transactions on Signal Processing, Circuits, Systems & Signal Processing, and an Editorial Board Member for International Journal of Computer Mathematics. Professor Wang is a Member of the Academia Europaea (section of Physics and Engineering Sciences), a Fellow of the IEEE (for contributions to networked control and complex networks), a Fellow of the Chinese Association of Automation, a Member of the IEEE Press Editorial Board, a Member of the EPSRC Peer Review College of the UK, a Fellow of the Royal Statistical Society, a member of program committee for many international conferences, and a very active reviewer for many international journals. He was nominated an appreciated reviewer for IEEE Transactions on Signal Processing in 2006- 2008 and 2011, an appreciated reviewer for IEEE Transactions on Intelligent Transportation Systems in 2008, an outstanding reviewer for IEEE Transactions on Automatic Control in 2004 and for the journal Automatica in 2000. Bo Shen received the B.Sc. degree in mathematics from Northwestern Polytechnical University, Xi'an, China, in 2003, and the Ph.D. degree in control theory and control engineering from Donghua University, Shanghai, China, in 2011. He is currently a Professor with the School of Information Science and Technology, Donghua University. From 2009 to 2010, he was a Research Assistant with the Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong. From 2010 to 2011, he was a Visiting Ph.D. Student with the Department of Information Systems and Computing, Brunel University London, London, U.K. From 2011 to 2013, he was a Research Fellow (Scientific Co-Worker) with the Institute for Automatic Control and Complex Systems, University of Duisburg-Essen, Duisburg, Germany. He has published around 80 articles in refereed international journals. His research interests include nonlinear control and filtering, stochastic control and filtering, as well as complex networks and neural networks. Prof. Shen serves (or has served) as an Associate Editor or Editorial Board Member for eight international journals, including Systems Science and Control Engineering, Journal of The Franklin Institute, Asian Journal of Control, Circuits, Systems, and Signal Processing, Neurocomputing, Assembly Automation, Neural Processing Letters, and Mathematical Problems in Engineering. He is a program committee member for many international conferences.