• DocumentCode
    1361731
  • Title

    A genetic algorithm modelling framework and solution technique for short term optimal hydrothermal scheduling

  • Author

    Orero, S.O. ; Irving, M.R.

  • Author_Institution
    Brunel Inst. of Power Syst., Brunel Univ., Uxbridge, UK
  • Volume
    13
  • Issue
    2
  • fYear
    1998
  • fDate
    5/1/1998 12:00:00 AM
  • Firstpage
    501
  • Lastpage
    518
  • Abstract
    A genetic algorithm is applied to the problem of determining the optimal hourly schedule of power generation in a hydrothermal power system. A multi-reservoir cascaded hydroelectric system with a nonlinear relationship between water discharge rate, net head and power generation is considered. The water transport delay between connected reservoirs is also taken into account. The main control parameters that affect the genetic algorithm performance are discussed and a summary of the theoretical basis of the genetic algorithm method is presented. It is shown that a multiple step genetic algorithm search sequence can provide the optimal hourly loading of the system generators
  • Keywords
    genetic algorithms; hydroelectric power stations; hydrothermal power systems; power system planning; scheduling; thermal power stations; control parameters; genetic algorithm; hydrothermal power system; multi-reservoir cascaded hydroelectric system; multiple step GA search sequence; net head; optimal hourly loading; planning optimisation; short-term power generation sheduling; water discharge rate; water transport delay; Genetic algorithms; Optimal scheduling; Power generation; Power generation economics; Power system control; Power system modeling; Power systems; Reservoirs; Water resources; Water storage;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/59.667375
  • Filename
    667375