Renewable energy sources interface with the ac grids via inverters are termed inverter-based resources (IBRs). They are replacing traditional fossil fuel-based synchronous generators at a dazzling speed. In turn, unprecedented dynamic events have occurred, threatening power grid reliability. Modeling and Stability Analysis of Inverter-Based Resources provides a fundamental understanding of IBR dynamics.
Developing reliability solutions requires a thorough understanding of challenges, and in this case, IBR-associated dynamics. Modeling and stability analysis play an indispensable role in revealing a mechanism of dynamics. This book covers the essential techniques of dynamic model building for IBRs, including type-3 wind farms, type-4 wind farms, and solar photovoltaics. Besides modeling, this book offers readers the techniques of stability analysis. The text includes three parts. Part 1 concentrates on tools, including electromagnetic transient simulation, analysis, and measurement-based modeling. Part 2 focuses on IBR modeling and analysis details. Part 3 highlights generalized dynamic circuit representation―a unified modeling framework for dynamic and harmonic analysis.
This topic of IBR dynamic modeling and stability analysis is interesting, challenging, and intriguing. The authors have led the effort of publishing the 2020 IEEE Power and Energy Society’s TR-80 taskforce report “Wind Energy Systems Subsynchronous Oscillations: Modeling and Events," and the two taskforce papers on investigation of real-world IBR dynamic events. In this book, the authors share with readers many insights into modeling and analysis for real-world IBR dynamic events investigation.
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Lingling Fan is Professor at the Department of Electrical Engineering at the University of South Florida (USF). Before joining the academia, she has worked in the grid operating industry Mid-west ISO for six years (2001-2007). She received the Bachelor of Science and Master of Science degrees in Electrical Engineering from Southeast University (Nanjing, China) in 1994 and 1997, respectively. She obtained the Ph.D. degree in Electrical Engineering from West Virginia University, Morgantown in 2001. Dr. Fan is research active in control, computing, and dynamic analysis of power systems, power electronics and electric machines. Her research has been sponsored by the Department of Energy, Midwest ISO, Duke Energy, National Science Foundation, Electric Power Research Institute, Florida Cyber Security Center, Jabil, etc. She has authored/co-authored two books Modeling and Analysis of Double Fed Induction Generator Wind Energy Systems (Elsevier Press, 2015) and Control and Dynamics in Power Systems and Microgrids (CRC press, 2017). Dr. Fan has served as Consulting Editor for IEEE transactions on Sustainable Energy. Currently, she serves as the Editor-in-Chief of IEEE Electrification Magazine and Associate Editor for IEEE transactions on Energy Conversion. She Fan was elevated to IEEE Fellow class 2022 for her contributions to stability analysis and control of inverter-based resources. She is the recipient of USF’s outstand- ing research achievement award in 2022 and has been featured in IEEE Power and Energy Society social media in March 2022 to celebrate World Engineering Day and National Women’s History Month.
Zhixin Miao is Professor at the Department of Electrical Engineering at the University of South Florida (USF). He received the Bachelor of Science in Electrical Engineering degree from the Huazhong University of Science and Technology at Wuhan China in 1992, the Master of Science in Electrical Engineering degree from the Graduate School, Nanjing Automation Research Institute (NARI) at Nanjing China in 1997, and the Ph.D. degree in electrical engineering from West Virginia University at Morgantown in 2002. He worked as a power system protection engineer from1992-1999 in NARI and a transmission planning engineer at Midwest ISO, St. Paul, MN, from 2002 to 2009. His research interests include digital twins, power system computer and hardware simulations, microgrids, and renewable energy integration. Dr. Miao serves as an associate editor for IEEE transactions on Sustainable Energy.
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Paperback. Condizione: new. Paperback. Renewable energy sources interface with the ac grids via inverters are termed inverter-based resources (IBRs). They are replacing traditional fossil fuel-based synchronous generators at a dazzling speed. In turn, unprecedented dynamic events have occurred, threatening power grid reliability. Modeling and Stability Analysis of Inverter-Based Resources provides a fundamental understanding of IBR dynamics.Developing reliability solutions requires a thorough understanding of challenges, and in this case, IBR-associated dynamics. Modeling and stability analysis play an indispensable role in revealing a mechanism of dynamics. This book covers the essential techniques of dynamic model building for IBRs, including type-3 wind farms, type-4 wind farms, and solar photovoltaics. Besides modeling, this book offers readers the techniques of stability analysis. The text includes three parts. Part 1 concentrates on tools, including electromagnetic transient simulation, analysis, and measurement-based modeling. Part 2 focuses on IBR modeling and analysis details. Part 3 highlights generalized dynamic circuit representationa unified modeling framework for dynamic and harmonic analysis.This topic of IBR dynamic modeling and stability analysis is interesting, challenging, and intriguing. The authors have led the effort of publishing the 2020 IEEE Power and Energy Societys TR-80 taskforce report Wind Energy Systems Subsynchronous Oscillations: Modeling and Events," and the two taskforce papers on investigation of real-world IBR dynamic events. In this book, the authors share with readers many insights into modeling and analysis for real-world IBR dynamic events investigation. Renewable energy sources interface with the ac grids via inverters and are termed inverter-based resources (IBRs). This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781032347493
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