• DocumentCode
    3089770
  • Title

    Equal Embedded Algorithm for Large Scale Economic Load Dispatch

  • Author

    Chandram, K. ; Subrahmanyam, N. ; Sydulu, M.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Inst. of Technol., Warangal
  • fYear
    2007
  • fDate
    24-28 June 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper presents a new algorithm called equal embedded algorithm is used to solve large scale economic load dispatch problem with prohibited zones and losses. The algorithm involves the selection of lambda values, then the output power expressions of generating unit are obtained in terms of the lambda by interpolation and finally the lambda is evaluated from the power balance equation by Muller method. The proposed algorithm was tested on a power system having 3, 6 and 20 generating units and the results were compared in terms of their solution quality, convergence characteristics and computation efficiency with the genetic algorithm, the two phase neural networks, the lambda iterative method and the particle swarm optimization method. Also the proposed algorithm was tested for large-scale system with 20 and 40 generating units. The proposed method gives minimum fuel cost with less computational time.
  • Keywords
    interpolation; iterative methods; large-scale systems; power generation dispatch; power generation economics; power system analysis computing; Muller method; equal embedded algorithm; interpolation; large scale economic load dispatch problem; power balance equation; power system; Character generation; Equations; Fuel economy; Interpolation; Iterative algorithms; Large-scale systems; Power generation; Power generation economics; Power systems; System testing; Economic Load Dispatch problem; Interpolation; Muller method; Quadratic Fuel Cost Function; Transmission Losses; prohibited zones; transmission losses;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2007. IEEE
  • Conference_Location
    Tampa, FL
  • ISSN
    1932-5517
  • Print_ISBN
    1-4244-1296-X
  • Electronic_ISBN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PES.2007.385611
  • Filename
    4275220