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230620s2023 sz s 0 eng d |
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|a9783031291005|q(electronic bk.)
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|
|a10.1007/978-3-031-29100-5|2doi
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|aeng
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|aTK3091
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|a621.319|223
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|aTK3091|b.X6 2023
|
100 |
1
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|aXie, Le.
|
245 |
10
|
|aData science and applications for modern power systems|h[electronic resource] /|cby Le Xie, Yang Weng, Ram Rajagopal.
|
260 |
|
|aCham :|bSpringer International Publishing :|bImprint: Springer,|c2023.
|
300 |
|
|axv, 436 p. :|bill., digital ;|c24 cm.
|
490 |
1
|
|aPower electronics and power systems,|x2196-3193
|
505 |
0
|
|aBig 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.
|
520 |
|
|aThis 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.
|
650 |
0
|
|aElectric power distribution|xData processing.
|
650 |
0
|
|aBig data.
|
650 |
14
|
|aElectrical Power Engineering.
|
650 |
24
|
|aBig Data.
|
650 |
24
|
|aIT in Business.
|
700 |
1
|
|aWeng, Yang.
|
700 |
1
|
|aRajagopal, Ram.
|
710 |
2
|
|aSpringerLink (Online service)
|
773 |
0
|
|tSpringer Nature eBook
|
830 |
0
|
|aPower electronics and power systems.
|
856 |
40
|
|uhttps://doi.org/10.1007/978-3-031-29100-5
|
950 |
|
|aEnergy (SpringerNature-40367)
|