• DocumentCode
    560857
  • Title

    A solution to dynamic economic dispatch with prohibited zones using a Hopfield neural network

  • Author

    Benhamida, Farid ; Bendaoued, Abdelber ; Medles, Karim ; Ayad, Abdelghani ; Tilmatine, Amar

  • Author_Institution
    Dept. of Electr. Eng., UDL Univ., Sidi Belabbes, Algeria
  • fYear
    2011
  • fDate
    1-4 Dec. 2011
  • Abstract
    A solution to the dynamic economic dispatch (DED) for 24-hour dispatch intervals (one day) with practical constraints using a Hopfield neural network (HNN) is proposed in this paper. The DED in this paper must satisfy the following constrained the system load demand, the spinning reserve capacity, the ramping rate limits and finally the prohibited operating zone. The feasibility of the proposed approach is demonstrated using two power systems, and it is compared with the other methods in terms of solution quality and computation efficiency.
  • Keywords
    Hopfield neural nets; power engineering computing; power generation dispatch; power generation economics; Hopfield neural network; dynamic economic dispatch; power systems; prohibited zones; ramping rate; spinning reserve capacity; system load demand; Economics; Generators; Genetic algorithms; Neurons; Power system dynamics; Propagation losses; Spinning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Electronics Engineering (ELECO), 2011 7th International Conference on
  • Conference_Location
    Bursa
  • Print_ISBN
    978-1-4673-0160-2
  • Type

    conf

  • Filename
    6140224