TY  - GEN
N2  - This book offers a comprehensive collection of research articles that utilize datain particular large data setsin 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.
DO  - 10.1007/978-3-031-29100-5
DO  - doi
AB  - This book offers a comprehensive collection of research articles that utilize datain particular large data setsin 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.
T1  - Data science and applications for modern power systems /
DA  - 2023.
CY  - Cham :
AU  - Xie, Le.
AU  - Weng, Yang.
AU  - Rajagopal, Ram.
CN  - TK3091
PB  - Springer,
PP  - Cham :
PY  - 2023.
N1  - Description based upon print version of record.
ID  - 1469949
KW  - Electric power distribution
KW  - Big data.
SN  - 9783031291005
SN  - 303129100X
TI  - Data science and applications for modern power systems /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-29100-5
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-29100-5
ER  -