• DocumentCode
    3255291
  • Title

    Transmission loss and load flow allocations via genetic algorithm technique

  • Author

    Sulaiman, Mohd Herwan ; Mustafa, Mohd Wazir ; Aliman, Omar

  • Author_Institution
    Sch. of Electr. Syst. Eng., Univ. Malaysia Perlis, Arau, Malaysia
  • fYear
    2009
  • fDate
    23-26 Jan. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Transmission loss and load flow allocations become important issues under deregulation system. Due to nonlinear nature of power flow, tracing the loss and power flow through the mesh network becomes more complicated. Since the complexity of electricity transmission system, it is not straightforward to determine the contribution of particular generator to a particular line loss and/ or load. This paper will discuss load flow and loss allocation using genetic algorithm (GA) technique. GA is one of the optimization techniques that apply natural phenomena, viz. genetic inheritance and Darwinian strive for survival. Transmission loss and load flow allocations problem will be treated as an optimization problem. In this paper, Ward-Hale 6-bus test system will be used to demonstrate the effectiveness of the technique and validated by IEEE 30-bus test system. Comparison with other method is also given.
  • Keywords
    genetic algorithms; load flow; power transmission; IEEE 30-bus test system; Ward-Hale 6-bus test system; electricity transmission system; genetic algorithm technique; load flow allocations; power flow; transmission loss; Artificial neural networks; Electricity supply industry deregulation; Genetic algorithms; Genetic engineering; Load flow; Power engineering and energy; Power generation; Propagation losses; System testing; Systems engineering and theory; deregulation; genetic algorithm (GA); load flow; transmission loss allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2009 - 2009 IEEE Region 10 Conference
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-4546-2
  • Electronic_ISBN
    978-1-4244-4547-9
  • Type

    conf

  • DOI
    10.1109/TENCON.2009.5396005
  • Filename
    5396005