• DocumentCode
    2248661
  • Title

    Artificial neural network for load forecasting in smart grid

  • Author

    Zhang, Hao-tian ; Xu, Fang-yuan ; Zhou, Long

  • Author_Institution
    Energy Syst. Group, City Univ. London, London, UK
  • Volume
    6
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    3200
  • Lastpage
    3205
  • Abstract
    It is an irresistible trend of the electric power improvement for developing the smart grid, which applies a large amount of new technologies in power generation, transmission, distribution and utilization to achieve optimization of the power configuration and energy saving. As one of the key links to make a grid smarter, load forecast plays a significant role in planning and operation in power system. Many ways such as Expert Systems, Grey System Theory, and Artificial Neural Network (ANN) and so on are employed into load forecast to do the simulation. This paper intends to illustrate the representation of the ANN applied in load forecast based on practical situation in Ontario Province, Canada.
  • Keywords
    artificial intelligence; load forecasting; neural nets; power engineering computing; power system planning; smart power grids; ANN; Canada; artificial neural network; load forecasting; planning; power system; smart grid; Artificial neural networks; Load forecasting; Load modeling; Meteorology; Neurons; Simulation; Training; Artificial Neuron Network; Load forecast; Matlab; back propagation training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5580713
  • Filename
    5580713