• DocumentCode
    2588925
  • Title

    A Genetic Algorithm Approach to Price-Based Unit Commitment

  • Author

    Solanki, Jignesh ; Khushalani, Sarika ; Srivastava, Anurag

  • Author_Institution
    Mississippi State Univ., Oxford, MS
  • fYear
    2006
  • fDate
    17-19 Sept. 2006
  • Firstpage
    425
  • Lastpage
    429
  • Abstract
    Deregulation creates competition amongst generator companies. The generator company objectives are to maximize their profit and to place proper bids in the market. In order to do this they need to determine the schedule and operating points based on the load and price forecasts. The traditional unit commitment problem aims at minimizing the cost of operation subject to fulfillment of demand. However in a deregulated environment the traditional unit commitment objective needs to be changed to maximization of profit with relaxation of the demand fulfillment constraint. This paper applies a genetic algorithm technique to price based unit commitment (PBUC) for GENCO with 3 generators and compares the solution with that obtained by dynamic programming. Proposed algorithm can be extended to ´n´ number of generators.
  • Keywords
    dynamic programming; genetic algorithms; load forecasting; power markets; electricity supply industry deregulation; genetic algorithm; load forecasting; price forecasting; price-based unit commitment; Availability; Costs; Demand forecasting; Dynamic programming; Economic forecasting; Genetic algorithms; Lagrangian functions; Load forecasting; Power system dynamics; Power systems; Price based unit commitment; deregulation; dynamic programming; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Symposium, 2006. NAPS 2006. 38th North American
  • Conference_Location
    Carbondale, IL
  • Print_ISBN
    1-4244-0227-1
  • Electronic_ISBN
    1-4244-0228-X
  • Type

    conf

  • DOI
    10.1109/NAPS.2006.359607
  • Filename
    4201350