• DocumentCode
    2295541
  • Title

    Identification of hydraulic turbine governor system parameters based on Bacterial Foraging Optimization Algorithm

  • Author

    Kou, Pangao ; Zhou, Jianzhong ; Li, Chaoshun ; He, Yaoyao ; He, Hui

  • Author_Institution
    Coll. of Hydroelectric Digitization Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • Volume
    7
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    3339
  • Lastpage
    3343
  • Abstract
    Hydraulic turbine generating unit plays an important role in power system. An accurate hydraulic turbine governor system model is essential to analyze its stability and dynamic performance. In order to identify the parameters of the hydraulic turbine governor system model, a new approach of Bacterial Foraging Optimization Algorithm (BFOA) is introduced in this study. To improve the precision of the identification process, a modified objective function is proposed based on the measurement of gate opening, mechanical torque and generator speed from a simulated model. The improved objective function (IOF) and the conventional objective function (COF) are used in the identification and two sets of parameters are derived and compared. The results show that BFOA is effective in identification of hydraulic turbine governor system and parameters derived from the modified objective function have a higher accuracy.
  • Keywords
    hydraulic turbines; hydroelectric generators; optimisation; power engineering computing; power system stability; BFOA; bacterial foraging optimization algorithm; gate opening; generator speed; hydraulic turbine generating unit; hydraulic turbine governor system; mechanical torque; objective function; power system; Hydraulic turbines; Microorganisms; Object oriented modeling; Object recognition; Parameter estimation; Torque; Bacterial Foraging Optimization Algorithm; Identification; governor system; hydraulic turbine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583639
  • Filename
    5583639