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Big data analytics framework for smart grids

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Big data analytics framework for smart gridsedited by R.K. Viral, Divya Asija and Surender Reddy Salkuti.
其他作者:	Viral, Rajkumar.
出版者:	Boca Raton, FL :CRC Press,2024.
面頁冊數:	1 online resource :ill.
標題:	Smart power grids.
電子資源:	https://www.taylorfrancis.com/books/9781032665399
ISBN:	9781032665399$q(electronic bk.)

Big data analytics framework for smart grids
Big data analytics framework for smart grids[electronic resource] /edited by R.K. Viral, Divya Asija and Surender Reddy Salkuti. - 1st ed. - Boca Raton, FL :CRC Press,2024. - 1 online resource :ill. - Explainable AI (XAI) for engineering applications. - Explainable AI (XAI) for engineering applications..

Includes bibliographical references and index.

The text comprehensively discusses smart grid operations and the use of big data analytics in overcoming the existing challenges. It covers smart power generation, transmission, and distribution, explains energy management systems, artificial intelligence, and machine learning-based computing. Presents a detailed state-of-the-art analysis of big data analytics and its uses in power grids Describes how the big data analytics framework has been used to display energy in two scenarios including a single house and a smart grid with thousands of smart meters Explores the role of the internet of things, artificial intelligence, and machine learning in smart grids Discusses edge analytics for integration of generation technologies, and decision-making approaches in detail Examines research limitations and presents recommendations for further research to incorporate big data analytics into power system design and operational frameworks The text presents a comprehensive study and assessment of the state-of-the-art research and development related to the unique needs of electrical utility grids, including operational technology, storage, processing, and communication systems. It further discusses important topics such as complex adaptive power system, self-healing power system, smart transmission, and distribution networks, and smart metering infrastructure. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology.

ISBN: 9781032665399$q(electronic bk.)Subjects--Topical Terms:

559143
Smart power grids.

LC Class. No.: TK3105

Dewey Class. No.: 621.31

Big data analytics framework for smart grids
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300 $a 1 online resource : $b ill.
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504 $a Includes bibliographical references and index.
520 $a The text comprehensively discusses smart grid operations and the use of big data analytics in overcoming the existing challenges. It covers smart power generation, transmission, and distribution, explains energy management systems, artificial intelligence, and machine learning-based computing. Presents a detailed state-of-the-art analysis of big data analytics and its uses in power grids Describes how the big data analytics framework has been used to display energy in two scenarios including a single house and a smart grid with thousands of smart meters Explores the role of the internet of things, artificial intelligence, and machine learning in smart grids Discusses edge analytics for integration of generation technologies, and decision-making approaches in detail Examines research limitations and presents recommendations for further research to incorporate big data analytics into power system design and operational frameworks The text presents a comprehensive study and assessment of the state-of-the-art research and development related to the unique needs of electrical utility grids, including operational technology, storage, processing, and communication systems. It further discusses important topics such as complex adaptive power system, self-healing power system, smart transmission, and distribution networks, and smart metering infrastructure. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology.
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