• DocumentCode
    2295801
  • Title

    Online strategy for scheduling a hydroelectric station

  • Author

    Ru, Hai ; Gao, Feng ; Guan, Xiaohong ; Zheng, Feifeng

  • Author_Institution
    State Key Lab. for Manuf. Syst. Eng., Xi´´an Jiaotong Univ., Xi´´an, China
  • fYear
    2012
  • fDate
    6-8 July 2012
  • Firstpage
    2479
  • Lastpage
    2484
  • Abstract
    The scheduling problem of reservoir hydroelectric station during the flood season caused major concern in academia and industry many years. Due to the uncertainty of flood, the schedule strategy should guarantee the enough flood prevention capacity of hydroelectric, meanwhile, a certain water head should also be kept in order to guarantee the power generation efficiency. Therefore, it´s a challenging to design the strategy of optimal scheduling for hydroelectric in flood season. This paper in response to this objective, online algorithm will be applied here to analysis optimal strategy, which manages the reservoir scheduling in terms of online strategy and competitive analysis. Then the evidence from Ankang reservoir are collected to test the competitive ratio of online strategy. The result and model of the study in this paper have guiding significance and reference value to decision makers facing the similar situation.
  • Keywords
    decision making; floods; hydroelectric power stations; power generation scheduling; reservoirs; Ankang reservoir; competitive analysis; decision makers; flood prevention capacity; flood season; flood uncertainty; online algorithm; online strategy; optimal scheduling strategy design; power generation efficiency; reservoir hydroelectric station scheduling problem; Educational institutions; Floods; Job shop scheduling; Laboratories; Optimal scheduling; Optimized production technology; Reservoirs; Competitive Ratio; Hydroelectric scheduling; Online Strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2012 10th World Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-1397-1
  • Type

    conf

  • DOI
    10.1109/WCICA.2012.6358290
  • Filename
    6358290