• DocumentCode
    3469227
  • Title

    Economic dispatch using simplified personal best oriented particle swarm optimizer

  • Author

    Chen, C.H.

  • Author_Institution
    Dept. of Electr. Eng., Tungnan Univ., Taipei
  • fYear
    2008
  • fDate
    6-9 April 2008
  • Firstpage
    572
  • Lastpage
    576
  • Abstract
    In this paper, the simplified personal best oriented particle swarm optimizer (SPPSO) is employed to solving economic power dispatch problem considering transmission losses. SPPSO is a simplified version of personal best oriented particle swarm optimizer (PPSO), stemming from particle swarm optimization (PSO). Although one term is eliminated from the velocity updating rule, the performance of SPPSO is not affected significantly, especially for small scale problems. Nevertheless, it gains the advantage of computation efficiency. The usefulness and capability of the proposed algorithm is verified via testing on three power systems having different numbers of committed generators. The optimal solutions obtained by the proposed method are compared with those obtained by other methods posted in literature. The results show that the proposed method indeed capable of obtaining high quality solutions quickly.
  • Keywords
    matrix algebra; particle swarm optimisation; power generation dispatch; power transmission economics; economic power dispatch problem; particle swarm optimizer; power system generators; power system testing; transmission losses; Ant colony optimization; Cost function; Fuel economy; Particle swarm optimization; Power demand; Power generation; Power generation economics; Power systems; Propagation losses; System testing; Economic Dispatch; Particle Swam Optimization; Transmission loss;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
  • Conference_Location
    Nanjuing
  • Print_ISBN
    978-7-900714-13-8
  • Electronic_ISBN
    978-7-900714-13-8
  • Type

    conf

  • DOI
    10.1109/DRPT.2008.4523471
  • Filename
    4523471