• DocumentCode
    2755431
  • Title

    Unit Commitment Using Particle Swarm-Based-Simulated Annealing Optimization Approach

  • Author

    Sadati, Nasser ; Hajian, Mahdi ; Zamani, Majid

  • Author_Institution
    Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran
  • fYear
    2007
  • fDate
    1-5 April 2007
  • Firstpage
    297
  • Lastpage
    302
  • Abstract
    In this paper, a new approach based on hybrid particle swarm-based-simulated annealing optimization (PSO-B-SA) for solving thermal unit commitment (UC) problems is proposed. The PSO-B-SA presented in this paper solves the two sub-problems simultaneously and independently; unit-scheduled problem that determines on/off status of units and the economic dispatch problem for production amount of generating units. Problem formulation of UC is defined as minimization of total objective function while satisfying all the associated constraints such as minimum up and down time, production limits and the required demand and spinning reserve. Simulation results show that the proposed approach can outperform the other solutions.
  • Keywords
    particle swarm optimisation; power generation dispatch; power generation economics; power generation scheduling; simulated annealing; thermal power stations; economic dispatch problem; particle swarm optimization; simulated annealing optimization; thermal unit commitment; unit-scheduled problem; Annealing; Costs; Dynamic programming; Hybrid intelligent systems; Linear programming; Particle swarm optimization; Power generation economics; Processor scheduling; Production; Spinning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Swarm Intelligence Symposium, 2007. SIS 2007. IEEE
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0708-7
  • Type

    conf

  • DOI
    10.1109/SIS.2007.367951
  • Filename
    4223188