• DocumentCode
    3230610
  • Title

    Application of particle swarm optimization in flood optimal control of reservoir group

  • Author

    Jian-qun, Wang ; Xu-Yang, Guo

  • Author_Institution
    Coll. of Hydrol. & Water Resources, Hohai Univ., Nanjing, China
  • fYear
    2010
  • fDate
    23-26 Sept. 2010
  • Firstpage
    856
  • Lastpage
    859
  • Abstract
    The reservoir group along the middle and lower reaches of Yellow River is composed of the Luhun reservoir, Guxian reservoir and Xiaolangdi reservoir, in addition to Huanyuankou hydrological station as the common flood control point, with each reservoir having its own flood control objective respectively. The flood protection priority of the reservoir group along the middle and lower reaches of Yellow River is to regulate flood scientifically and reduce peak discharge at the flood control points of every reservoir and Huanyuankou hydrological station in the most efficient way. A flood optimal control model is established to optimize flood control of the reservoir group along the middle and lower reaches of Yellow River, based on the maximum flood peak clipping criterion. The combination of particle swarm optimization with reservoir cycling method is proposed to solve the model, whose effectiveness is validated through an expirical study.
  • Keywords
    floods; nonlinear programming; optimal control; particle swarm optimisation; reservoirs; Guxian reservoir; Huanyuankou hydrological station; Luhun reservoir; Xiaolangdi reservoir; Yellow River; flood optimal control; maximum flood peak clipping criterion; nonlinear optimization; particle swarm optimization; reservoir cycling method; reservoir group; Integrated optics; Reservoirs; flood regulation; nonlinear optimization; optimal operation; particle swarm optimization; swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-6437-1
  • Type

    conf

  • DOI
    10.1109/BICTA.2010.5645237
  • Filename
    5645237