• DocumentCode
    2059860
  • Title

    Fast bounding technique for branch-and-cut algorithm based monthly SCUC

  • Author

    Peng Wang ; Yang Wang ; Qing Xia

  • Author_Institution
    Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Monthly unit commitment with energy constraints is crucial for reducing the energy consumption of generation scheduling. Restricted by the calculation complexity, most approaches for long-term SCUC have to sacrifice the optimality of the solution for the sake of the acceptable calculation time. In response to this issue, a fast bounding technique is proposed to improve the traditional branch and cut algorithm. This technique is able to quickly decrease the upper bound and increase the lower bound for the optimal solution of long-term SCUC in branch-and-cut search, and improve the calculation speed of monthly SCUC in the premise of guaranteeing the optimality of solution. A practical provincial power system in China is employed in cases study, and corresponding results demonstrate the effectiveness of the proposed algorithm.
  • Keywords
    computational complexity; power generation dispatch; power generation scheduling; power system security; search problems; branch-and-cut search; calculation complexity; energy constraints; energy consumption reduction; fast bounding technique; generation scheduling; long-term SCUC; monthly SCUC; monthly unit commitment; provincial power system; security constrained unit commitment; Algorithm design and analysis; Fuels; Heuristic algorithms; Power generation; Power system dynamics; Upper bound; Branch-and-cut algorithm; cut plane technique; energy constraints; energy efficiency; long-term; mixed integer program (MIP); security constrained unit commit-ment (SCUC);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6345349
  • Filename
    6345349