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Green Machine Learning and Big Data for Smart Grids: Practices and Applications

Contributor(s): Indragandhi, V (Editor), Elakkiya, R (Editor), Subramaniyaswamy, V (Editor)

ISBN: 9780443289514

Publisher: Elsevier

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Pub Date: November 13, 2024

Lexile Code: 0000

Target Age Group: NA to NA

Physical Info: 0.67" H x 9.00" L x 6.00" W ( 0.94 lbs) 400 pages

Series: Advances in Intelligent Energy Systems

Descriptions, Reviews, etc.

Description: 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.

Brief description:

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.

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