Enhancing Resilience in Distribution Systems - Li, Fangxing Fran; Shi, Qingxin; Zhao, Jin
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Enhancing Resilience in Distribution Systems presents practical guidance for readers on the challenges and potential solutions for resilience in modern power systems. The book begins by explaining the risks and problems for resilience presented by renewable-based power systems. It goes on to clarify the current state of research and propose several novel methodologies and technologies for analysis and improvement of power system resilience. These methods include deep learning, linear programming, and generative adversarial networks. Packed with practical steps and tools for implementing the…mehr

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Produktbeschreibung
Enhancing Resilience in Distribution Systems presents practical guidance for readers on the challenges and potential solutions for resilience in modern power systems. The book begins by explaining the risks and problems for resilience presented by renewable-based power systems. It goes on to clarify the current state of research and propose several novel methodologies and technologies for analysis and improvement of power system resilience. These methods include deep learning, linear programming, and generative adversarial networks. Packed with practical steps and tools for implementing the latest technologies, this book provides researchers and industry professionals with guidance on the resilient systems of the future.
Autorenporträt
Fangxing 'Fran' Li is the James W. McConnell Professor in Electrical Engineering and the Campus Director of CURENT at the University of Tennessee at Knoxville, USA. His current research interests include resilience, artificial intelligence in power, demand response, distributed generation and microgrid, and energy markets. From 2020 to 2021, he served as the Chair of the IEEE PES Power System Operation, Planning and Economics (PSOPE) Committee. He has been the Chair of IEEE WG on Machine Learning for Power Systems since 2019 and the Editor-In-Chief of IEEE Open Access Journal of Power and Energy (OAJPE) since 2020. Prof. Li has received numerous awards and honours including R&D 100 Award in 2020, IEEE PES Technical Committee Prize Paper award in 2019, 5 best or prize paper awards at international journals, and 6 best papers/posters at international conferences.