• DocumentCode
    285172
  • Title

    Neural networks for generation scheduling in power systems

  • Author

    Liu, Z.J. ; Villaseca, F.E. ; Renovich, F., Jr.

  • Author_Institution
    Dept. of Electr. Eng., Cleveland State Univ., OH, USA
  • Volume
    2
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    233
  • Abstract
    A neural network for generation scheduling in power systems is presented. The network consists of two levels which correspond to different types of variables in the generation scheduling problem. The first level is a neural net which solves economic dispatch, a sub-problem in the generation scheduling problem. Its outputs indicate the power generation of generating units. The second level is a Boltzmann machine, a stochastic neural net which determines the off/on status of units. Simulation on a 20 generating-unit system shows that fast and optimal solutions can be obtained using the proposed neural network
  • Keywords
    Boltzmann machines; power system computer control; Boltzmann machine; economic dispatch; generation scheduling; neural networks; power systems; simulation; stochastic neural net; Computational modeling; Costs; Intelligent networks; Neural networks; Power generation; Power generation economics; Power systems; Processor scheduling; Production systems; Spinning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.227002
  • Filename
    227002