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Data Science and Applications for Modern Power Systems / by Le Xie, Yang Weng, Ram Rajagopal.

Springer eBooks EBA - Energy Collection 2023 Available online

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Format:
Book
Author/Creator:
Xie, Le.
Contributor:
Weng, Yang.
Rajagopal, Ram.
Series:
Power Electronics and Power Systems, 2196-3193
Language:
English
Subjects (All):
Electric power production.
Big data.
Business information services.
Electrical Power Engineering.
Big Data.
IT in Business.
Local Subjects:
Electrical Power Engineering.
Big Data.
IT in Business.
Physical Description:
1 online resource (446 pages)
Edition:
1st ed. 2023.
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2023.
Summary:
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.
Contents:
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.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-031-29100-X
OCLC:
1385454934

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