• DocumentCode
    1144679
  • Title

    Fast evolutionary programming techniques for short-term hydrothermal scheduling

  • Author

    Sinha, Nidul ; Chakrabarti, R. ; Chattopadhyay, P.K.

  • Author_Institution
    Dept. of Electr. Eng., Jadavpur Univ., Kolkata, India
  • Volume
    18
  • Issue
    1
  • fYear
    2003
  • fDate
    2/1/2003 12:00:00 AM
  • Firstpage
    214
  • Lastpage
    220
  • Abstract
    Fast evolutionary programming techniques are applied for the solution of a short-term hydrothermal scheduling problem. Evolutionary programming (EP)-based algorithms with Gaussian and other mutation techniques have been developed and tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and a thermal unit with valve point loading. Numerical results show that all of the EP algorithms are capable of finding very nearly global solutions within a reasonable time but an EP algorithm with better of Gaussian and Cauchy mutations appears to be the best amongst all EPs in terms of convergence speed, solution time, and minimum cost.
  • Keywords
    evolutionary computation; hydroelectric power stations; hydrothermal power systems; power generation planning; power generation scheduling; thermal power stations; Cauchy mutations; Gaussian techniques; convergence speed; fast evolutionary programming techniques; minimum cost; multi-reservoir cascaded hydroelectric system; mutation techniques; prohibited operating zones; short-term hydrothermal scheduling; solution time; thermal generating unit; valve point loading; Costs; Genetic mutations; Genetic programming; Optimal scheduling; Power generation; Power generation economics; Production; Reservoirs; Thermal loading; Water resources;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2002.807053
  • Filename
    1178799