AI for Power Electronics and Renewable Energy Systems

Inbunden, Engelska, 2024

1 703 kr

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Beskrivning

Rising shares of renewable energy are needed to stave off catastrophic climate change, but also bring about the challenge of intermittency, jeopardizing power quality. Instead of large central generation units, many distributed generators and loads need to be managed in order to integrate renewable energy with power systems.Artificial intelligence (AI) can meet this challenge with adaptive control and demand side management. When managing distributed and changing network components, AI can give control computers human-level performance, helping to solve key issues with intermittency, power quality and distributed generation and loads including EV. Use of AI for power systems has therefore become a research hotspot.This reference book systematically treats the applications of AI in power electronics and renewable energy systems. The book begins with an introduction to AI in power systems, then subsequent chapters cover the use of AI for electric machine fault diagnosis, for power electronic reliability, design, and control, in dual-active-bridge converters; AI for distribution network voltage control, signal stability control, and energy management of hybrid systems as well as for renewable energy systems with AI. The book ends with conclusions and an outlook for AI in power systems. Numerous worked examples throughout the text help readers understand the operating and controlling guidelines.Written by a team of well-known scientists and power system experts, AI for Power Electronics and Renewable Energy Systems is a valuable resource for researchers and PhD students, as well as experts in industry and utilities involved with electric power systems.

Produktinformation

Utgivningsdatum:2024-07-23
Mått:156 x 234 x 21 mm
Vikt:658 g
Format:Inbunden
Språk:Engelska
Serie:Energy Engineering
Antal sidor:346
Förlag:Institution of Engineering and Technology
ISBN:9781839537745

Utforska kategorier

Energiteknik inom Naturvetenskap och teknik
Artificiell intelligens inom Data och IT

Mer om författaren

Weihao Hu is a full professor at the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China. He has participated in several national and international research projects and authored more than 200 publications in his technical field, which has been cited over 8,000 times. His research interests include intelligent energy systems and renewable power generation. Dr Hu is an IET fellow and a senior member of IEEE. Dr Hu is an associate editor for IET Renewable Power Generation and Journal of Modern Power Systems and Clean Energy. He served as the conference chair, conference co-chair, and technical program chair for several IEEE conferences and he is currently serving as the chair for IEEE Chengdu Section PELS Chapter.Guozhou Zhang is a lecturer at the College of Engineering and Technology, Southwest University, China. He received his PhD degree from the University of Electronic Science and Technology of China, Chengdu, China, in 2022. He has published more than 30 peer-reviewed journal papers. His research interests include energy management, reinforcement learning, wind farm control, distributed energy systems, power stability, and energy storage control.Zhenyuan Zhang is a professor at the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China. Since 2010, he has been the project associate for the IEEE/NFPA Arc Flash Research Project. A senior member of IEEE, his research interests include power system analysis and power system optimization, but he has also been involved in smart grids, renewable energy, electrical safety analysis, arc flash analysis, and power market research works.Sayed Abulanwar is an associate professor at the Electrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt. He is also with the Faculty of Engineering, Horus University-Egypt. Dr Abulanwar is a senior member of IEEE. He received the BSc and MSc degrees in electrical engineering from Mansoura University, Mansoura, Egypt, in 2005 and 2010, respectively, and the PhD degree from the Energy Technology Department, Aalborg University, Denmark, in 2016. He is an associate editor for IET Renewable Power Generation and Alexandria Engineering Journal, and guest editor for IET Renewable Power Generation for Special Issue: Applications of Artificial Intelligence in Renewable Energy Systems. He is also a guest editor of the Special Issue: Planning and Operation of Hybrid Renewable Energy Systems, Volume II, Frontiers in Energy Research. He has participated in several national and international research projects. His research interests include hybrid AC/DC microgrids, intelligent energy systems, protection of AC and DC systems, wind energy conversion systems and grid-connected converters.Frede Blaabjerg is a full professor at the Faculty of Engineering and Science of Aalborg University, Denmark. Prior positions include ABB-Scandia. His current research interests include power electronics and its applications such as in wind turbines, PV systems, reliability, harmonics, and adjustable speed drives. He has authored more than 800 journal papers on power electronics and its applications, he is co-author of six monographs and editor of 15 books. He has received 40 IEEE paper awards and numerous distinguished international research awards. He has been the President of the IEEE Power Electronics Society.

Innehållsförteckning

Chapter 1: Introduction to AI in power systemChapter 2: Artificial intelligence for electric machine fault diagnosisChapter 3: Artificial intelligence in power electronic reliability, design, and controlChapter 4: Application of artificial intelligence in dual-active-bridge (DAB) convertersChapter 5: An active distribution network voltage control using artificial intelligenceChapter 6: Energy management of hybrid systems using artificial intelligenceChapter 7: Artificial intelligence in energy management of microgridChapter 8: Artificial intelligence in renewable energy systems small signal stability controlChapter 9: Conclusions and outlook using AI in power systems