• DocumentCode
    1609413
  • Title

    Economic load flow using Lagrange neural network

  • Author

    Mohatram, Mohammad ; Tewari, Peeyush ; Latanath, Nutan

  • Author_Institution
    Waljat Coll. of Appl. Sci., Muscat, Oman
  • fYear
    2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This paper proposed an artificial neural network (ANN) approach based on Lagrangian multiplier method (Lagrangian ANN) to solve the problem of economic load flow in a power system. Operational requirements and transmission losses are also taken care by the proposed approach. Power plant operating costs are represented by exponential cost functions. Simulation on a test example with six generating units shows that the proposed method can efficiently and accurately solve the problem of economic load flow.
  • Keywords
    load flow; neural nets; power generation economics; power generation scheduling; power system analysis computing; Lagrange neural network; Lagrangian multiplier; artificial neural network; economic load flow; exponential cost functions; power plant operating costs; transmission loss; Artificial neural networks; Biological system modeling; Convergence; Economics; Fuels; Load flow; Mathematical model; Lagrangian ANN; economic generation scheduling; exponentia l cost function; load flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Communications and Photonics Conference (SIECPC), 2011 Saudi International
  • Conference_Location
    Riyadh
  • Print_ISBN
    978-1-4577-0068-2
  • Electronic_ISBN
    978-1-4577-0067-5
  • Type

    conf

  • DOI
    10.1109/SIECPC.2011.5876896
  • Filename
    5876896