• DocumentCode
    3714944
  • Title

    The application of System Identification via Canonical Variate Algorithm to North Benghazi gas turbine Power generation system

  • Author

    Omar Mohamed;Ashraf Khalil;Marwan Limhabrash; Jihong Wang

  • Author_Institution
    Electrical Engineering Department, Princess Sumaya University of Technology, P. O. BOX: 1438, Amman - Jordan
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The topic of modeling and identification of gas turbines has become an interesting research area for many years and will become so for many years to come. This paper clarifies what is known as Canonical Variate Algorithm or canonical variate analysis (CVA) method of subspace state space system identification. A gas turbine operating currently in North Benghazi Power Plant (NBPP) is the process chosen to be our focus of study in the paper. The CVA is described from mathematics and linear algebra view points. The process of gas turbine under investigation is illustrated and discussed. Through gathered operating data from the power plant under study and MATLAB System Identification Toolbox, the state space model is developed and tested against different data signals. Simulation results have shown the robustness and the accuracy of the presented method of identification.
  • Keywords
    "Object recognition","Covariance matrices","Yttrium","Combustion","Turbines"
  • Publisher
    ieee
  • Conference_Titel
    Applied Electrical Engineering and Computing Technologies (AEECT), 2015 IEEE Jordan Conference on
  • Print_ISBN
    978-1-4799-7442-9
  • Type

    conf

  • DOI
    10.1109/AEECT.2015.7360556
  • Filename
    7360556