• DocumentCode
    3486476
  • Title

    Comparison of two heuristic approaches to hydro unit commitment

  • Author

    Ohishi, T. ; Santos, E. ; Arce, A. ; Kadowaki, M. ; Cicogna, M. ; Soares, S.

  • Author_Institution
    State Univ. of Campinas, Campinas
  • fYear
    2005
  • fDate
    27-30 June 2005
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This paper is concerned with the unit commitment of hydro generating units on an hourly basis throughout a single day. The performance criterion to be optimized includes the efficiency of hydro conversion, which depends on variations in tailrace elevation, penstock head losses and turbine-generator efficiency, as well as the cost of startup/shutdown of the hydro generating units. The paper presents a comparison of two heuristic approaches for solving the optimization problem. One heuristic is based on decomposing the problem into Generation Scheduling (GS) and Unit Scheduling (US) sub-problems, and solving the sub-problems by Lagrangian Relaxation and Dynamic Programming, respectively. The other heuristic makes use of a Genetic Algorithm combined with Lagrangian Relaxation to solve the original problem. The two heuristics were tested on a system composed of sixteen hydro plants, one hundred generating units, and an installed capacity of 21,933 MW in the Brazilian power system. The actual scheduling of generation actual for a typical day was used for comparison with the solutions proposed by the two heuristics. The results of both heuristics show significant savings in terms of hydro conversion efficiency and startup/shutdown costs.
  • Keywords
    genetic algorithms; hydroelectric power; power system economics; power system reliability; Lagrangian relaxation; dynamic programming; generation scheduling; genetic algorithm; heuristic approaches; hydro conversion efficiency; hydro generating units; hydro unit commitment; optimization problem; power 21933 MW; startup/shutdown costs; unit scheduling; Cost function; Dynamic programming; Dynamic scheduling; Genetic algorithms; Lagrangian functions; Performance loss; Power generation; Power system dynamics; Power systems; System testing; Dynamic Programming; Genetic Algorithm; Heuristics; Hydro unit commitment; Lagrangian Relaxation; hydro efficiency conversion; startup/shutdown cost;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Tech, 2005 IEEE Russia
  • Conference_Location
    St. Petersburg
  • Print_ISBN
    978-5-93208-034-4
  • Electronic_ISBN
    978-5-93208-034-4
  • Type

    conf

  • DOI
    10.1109/PTC.2005.4524670
  • Filename
    4524670