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Deep neural networks for short-term load forecasting in ERCOT system

  • Mitchell Easley
  • , Luke Haney
  • , Jose Paul
  • , Kim Fowler
  • , Hongyu Wu
  • Kansas State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original languageEnglish
Title of host publication2018 IEEE Texas Power and Energy Conference, TPEC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538610060
DOIs
StatePublished - Mar 9 2018
Externally publishedYes
Event2nd IEEE Texas Power and Energy Conference, TPEC 2018 - College Station, United States
Duration: Feb 8 2018 → Feb 9 2018

Publication series

Name2018 IEEE Texas Power and Energy Conference, TPEC 2018
Volume2018-February

Conference

Conference2nd IEEE Texas Power and Energy Conference, TPEC 2018
Country/TerritoryUnited States
CityCollege Station
Period2/8/18 → 2/9/18

ASJC Scopus Subject Areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

Keywords

  • Bayesian Regularization
  • deep learning
  • Levenberg-Marquardt
  • Load forecast
  • neural network
  • Scaled Conjugate Gradient

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