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Energy management : big data in power load forecasting / Valentin A. Boicea.

By: Material type: TextPublisher: Boca Raton, FL : CRC Press, 2021Edition: First editionDescription: 1 online resource (1 volume) : illustrations (black and white)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781000437683
  • 100043768X
  • 9781003147213
  • 1003147216
  • 9781000437812
  • 1000437817
Subject(s): DDC classification:
  • 621.042 23
LOC classification:
  • TJ163.2
Online resources: Summary: This book introduces the principle of carrying out a medium-term load forecast (MTLF) at power system level, based on the Big Data concept and Convolutionary Neural Network (CNNs). It also presents further research directions in the field of Deep Learning techniques and Big Data, as well as how these two concepts are used in power engineering. Efficient processing and accuracy of Big Data in the load forecast in power engineering leads to a significant improvement in the consumption pattern of the client and, implicitly, a better consumer awareness. At the same time, new energy services and new lines of business can be developed. The book will be of interest to electrical engineers, power engineers, and energy services professionals.
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This book introduces the principle of carrying out a medium-term load forecast (MTLF) at power system level, based on the Big Data concept and Convolutionary Neural Network (CNNs). It also presents further research directions in the field of Deep Learning techniques and Big Data, as well as how these two concepts are used in power engineering. Efficient processing and accuracy of Big Data in the load forecast in power engineering leads to a significant improvement in the consumption pattern of the client and, implicitly, a better consumer awareness. At the same time, new energy services and new lines of business can be developed. The book will be of interest to electrical engineers, power engineers, and energy services professionals.

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