Green Machine Learning and Big Data for Smart Grids : Practices and Applications
Language: English
Published by Elsevier Inc Nov 2024, 2024
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Add to basketItem description from seller
Neuware - Green Machine Learning and Big Data for Smart Grids: Practices and Applications is a guidebook to the best practices and potential for green data analytics when generating innovative solutions to renewable energy integration in the power grid. This book begins with a solid foundation in the concept of green machine learning and the essential technologies for utilizing data analytics in smart grids. A variety of scenarios are examined closely, demonstrating the opportunities for supporting renewable energy integration using machine learning, from forecasting and stability prediction to smart metering and disturbance tests.Uses for control of physical components including inverters and converters are examined, along with policy implications. Importantly, real-world case studies and chapter objectives are combined to signpost essential information, and to support understanding and implementation.
Seller Inventory # 9780443289514
- Title
- Green Machine Learning and Big Data for Smart Grids : Practices and Applications
- Author
- V. Subramaniyaswamy
- Publisher
- Elsevier Inc Nov 2024
- Publication year
- 2024
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0443289514
- ISBN 13
- 9780443289514
- Item weight
- 429 grams
- Dimensions
- 229x152x17 mm
Uses for control of physical components including inverters and converters are examined, along with policy implications. Importantly, real-world case studies and chapter objectives are combined to signpost essential information, and to support understanding and implementation.
- Packages core concepts of green machine learning and smart grids in a clear, understandable way
- Includes real-world, practical applications and case studies for replication and innovative solution development
- Introduces readers with a range of expertise to best practices and the latest technological advances
"Synopsis" may belong to another edition of this title.
About the Author
Dr. V. Indragandhi is a Professor in the School of Electrical Engineering, Department of Energy and Power Electronics, at Vellore Institute of Technology (VIT), Vellore. Her areas of specialization include power electronics, advanced semiconductor devices, energy storage, artificial intelligence, and electric vehicles.
Dr. R. Elakkiya is an Assistant Professor in the Department of Computer Science, Birla Institute of Technology & Science, Pilani, Dubai Campus. She received her PhD from Anna University, Chennai, in 2018. She secured the University First Rank and was awarded the Gold Medal during master’s in software engineering from CEG Campus, Anna University, Chennai. She won the iDEX - DISC 4 challenge and received the grant award from DIO, DRDO in 2021 and Young Achiever Award from INSc in 2019. She had received many extra-mural funded projects from various government and non-government agencies and served as Machine Learning and Data Analytics Consultant and delivered many products to different industry verticals. She is Member of the Association of Computing Machinery and Lifetime Member of International Association of Engineers.
Dr V. Subramaniyaswamy is currently working as a Professor in the School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India. In total, he has 18 years of experience in academia. He has published papers in reputed international journals and conferences and filed multiple patents. His technical competencies lie in recommender systems, Artificial Intelligence, the Internet of Things, reinforcement learning, big data analytics, and cognitive analytics. He has edited Electric Motor Drives and their Applications, with Simulation Practice (Elsevier: 2022, ISBN: 9780323911627), among other books.
"About the title" may belong to another edition of this title.
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