• DocumentCode
    1378204
  • Title

    A profit-based unit commitment GA for the competitive environment

  • Author

    Richter, Charles W., Jr. ; Sheblé, Gerald B.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
  • Volume
    15
  • Issue
    2
  • fYear
    2000
  • fDate
    5/1/2000 12:00:00 AM
  • Firstpage
    715
  • Lastpage
    721
  • Abstract
    As the electrical industry restructures, many of the traditional algorithms for controlling generating units need modification or replacement, previously utilized to schedule generation units in a manner that minimizes costs while meeting all demand, the unit commitment (UC) algorithm must be updated. A UC algorithm that maximizes profit will play an essential role in developing successful bidding strategies for the competitive generator. Simply bidding to win contracts is insufficient; bidding strategies must result in contracts that, on average, cover the total generation costs. No longer guaranteed to be the only electricity supplier, a generation company´s share of the demand will be more difficult to predict than in the past. Removing the obligation to serve softens the demand constraint. In this paper the authors provide a price/profit-based UC formulation which considers the softer demand constraint and allocates fixed and transitional costs to the scheduled hours. The authors describe a genetic algorithm solution to this new UC problem and present results for an illustrative example
  • Keywords
    electricity supply industry; genetic algorithms; power generation economics; power generation scheduling; bidding strategies; competitive environment; competitive generator; costs minimization; demand constraint; fixed costs allocation; generating units control; generation units scheduling; profit-based unit commitment; transitional costs allocation; unit commitment algorithm; Contracts; Costs; Electricity supply industry deregulation; Genetic algorithms; Helium; Industrial control; Job shop scheduling; Power generation; Power systems; Scheduling algorithm;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/59.867164
  • Filename
    867164