• DocumentCode
    3696518
  • Title

    Economic Dispatch using Improved Hopfield Neural Network

  • Author

    S. Surender Reddy;James A. Momoh

  • Author_Institution
    Department of Railroad &
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents an Improved Hopfield Neural Network (IHNN) to solve the Economic Dispatch (ED) problem. In this paper, an attempt has been made to implement Artificial Neural Networks (ANN) for Economic Load Dispatch problem. In this ED model, the transmission system and active power constraints are included. The proposed IHNN model has fast convergence and moves efficiently towards feasible equilibrium points. The ED using proposed IHNN has been tested on 3, 6 and 20 generating units. The results obtained with Improved HNN are compared with those of the results obtained by Lambda iteration method and Particle Swarm Optimization. The findings confirmed the robustness, proficiency and fast convergence of the proposed approach over other existing techniques.
  • Keywords
    "Generators","Hopfield neural networks","Economics","Fuels","Propagation losses","Power generation"
  • Publisher
    ieee
  • Conference_Titel
    North American Power Symposium (NAPS), 2015
  • Type

    conf

  • DOI
    10.1109/NAPS.2015.7335246
  • Filename
    7335246