• DocumentCode
    3283084
  • Title

    Two-Stage Multi-objective Unit Commitment Optimization under Future Load Uncertainty

  • Author

    Bo Wang ; You Li ; Watada, Junzo

  • Author_Institution
    Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan
  • fYear
    2012
  • fDate
    25-28 Aug. 2012
  • Firstpage
    128
  • Lastpage
    131
  • Abstract
    The unit commitment problem is to reduce the total generation cost as much as possible while satisfying future power demands. Therefore, optimization must be performed based on correct predictions of future demands. However, various uncertain factors affect these loads making an exact forecasting unsuccessful. This study mitigates this difficulty by applying fuzzy set theory and the objective is to build a two-stage multi-objective fuzzy programming model. to define the supply reliability effectively, we propose a new concept of maximal blackout time based on the fuzzy credibility theory. in addition, an improved two-layer multi-objective particle swarm optimization algorithm is designed as the solution. Finally, the performance of this study is discussed in comparison with experimental results from several test systems.
  • Keywords
    fuzzy set theory; particle swarm optimisation; power generation dispatch; power generation scheduling; future load uncertainty; fuzzy credibility theory; fuzzy set theory; total generation cost; two-layer multiobjective particle swarm optimization algorithm; two-stage multiobjective fuzzy programming model; two-stage multiobjective unit commitment optimization; Cost function; Equations; Mathematical model; Particle swarm optimization; Reliability; Schedules; Fuzzy set theory; Load uncertainty; Maximal blackout time; Particle swarm optimization algorithm; Two-stage multiobjective;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
  • Conference_Location
    Kitakushu
  • Print_ISBN
    978-1-4673-2138-9
  • Type

    conf

  • DOI
    10.1109/ICGEC.2012.147
  • Filename
    6457196