Bokus
Ali Tajer, Samir M. Perlaza, H. Vincent Poor - Advanced Data Analytics for Power Systems, Inbunden

Inbunden, Engelska, 2021

Advanced Data Analytics for Power Systems

Av Ali Tajer, Samir M. Perlaza, H. Vincent Poor

1517 kr

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Beskrivning
Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical learning, big data analytics, graph theory, and game theory, this is an essential resource for graduate students and researchers in academia and industry with backgrounds in power systems engineering, applied mathematics, and computer science.
Produktinformation
  • Utgivningsdatum: 2021-04-08
  • Mått: 175 x 251 x 34 mm
  • Vikt: 1 260 g
  • Format: Inbunden
  • Språk: Engelska
  • Antal sidor: 598
  • Förlag: Cambridge University Press
  • ISBN: 9781108494755
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Mer om författaren

Ali Tajer is Associate Professor of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute. Samir M. Perlaza is a research scientist with the Institut National de Recherche en Informatique, Automatique et Mathématiques Appliquées (INRIA), France, and a visiting research scholar at the Department of Electrical Engineering of Princeton University. H. Vincent Poor is the Michael Henry Strater University Professor of Electrical Engineering at Princeton University. He is a member of the US National Academy of Engineering, the US National Academy of Sciences, and a Fellow of the IEEE.

Recensioner i media

'There are only a few industries that generate an equally large amount of data with a comparable variety, and societal importance. Data analytics is thus rightfully at the heart of modern power systems operations and planning. Focusing on applications in power systems, this book gives an excellent account of recent developments and of the broad range of algorithms and tools in the area of data analytics, as well as of the applications of these tools for solving challenging problems from a novel angle. Covering a wide range of fundamental problems, from state estimation to load scheduling and anomaly detection, the book is not only an excellent source of inspiration, but can also serve as an extensive reference for the gamut of operational problems faced in the power industry.' György Dán, KTH Royal Institute of Technology

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