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Data science and applications for mo...

Weng, Yang.

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Data science and applications for modern power systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data science and applications for modern power systems/ by Le Xie, Yang Weng, Ram Rajagopal.
作者:	Xie, Le.
其他作者:	Weng, Yang.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	xv, 436 p. :ill., digital ;24 cm.
內容註:	Big Data Challenges in Power Systems -- Challenges and Opportunities in Utility Data -- Wholesale Markets Data Deluge -- Distribution System Data Operation -- Synchrophasor Data Analytics -- Smart Meter and its Implications -- Deep Learning in Power Markets -- Data-driven Planning in Electric Energy Systems -- Common Information Model for Unifying Data Sets -- Inference and Business for Aggregators Non-intrusive Load Monitoring -- Utility Business Model in the Era of Big Data -- Data Security Services for Utilities.
Contained By:	Springer Nature eBook
標題:	Electric power distribution - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-031-29100-5
ISBN:	9783031291005

Data science and applications for modern power systems
Xie, Le.

Data science and applications for modern power systems[electronic resource] /by Le Xie, Yang Weng, Ram Rajagopal. - Cham :Springer International Publishing :2023. - xv, 436 p. :ill., digital ;24 cm. - Power electronics and power systems,2196-3193. - Power electronics and power systems..

Big Data Challenges in Power Systems -- Challenges and Opportunities in Utility Data -- Wholesale Markets Data Deluge -- Distribution System Data Operation -- Synchrophasor Data Analytics -- Smart Meter and its Implications -- Deep Learning in Power Markets -- Data-driven Planning in Electric Energy Systems -- Common Information Model for Unifying Data Sets -- Inference and Business for Aggregators Non-intrusive Load Monitoring -- Utility Business Model in the Era of Big Data -- Data Security Services for Utilities.

This book offers a comprehensive collection of research articles that utilize data-in particular large data sets-in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid. Presents a comprehensive review of data sciences for the power industry; Contains state-of-the-art research articles; Provides practical algorithms and case studies.

ISBN: 9783031291005

Standard No.: 10.1007/978-3-031-29100-5doiSubjects--Topical Terms:

2153241
Electric power distribution
--Data processing.

LC Class. No.: TK3091

Dewey Class. No.: 621.319

Data science and applications for modern power systems
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520 $a This book offers a comprehensive collection of research articles that utilize data-in particular large data sets-in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid. Presents a comprehensive review of data sciences for the power industry; Contains state-of-the-art research articles; Provides practical algorithms and case studies.
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