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
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"
Conference_Titel :
Applied Electrical Engineering and Computing Technologies (AEECT), 2015 IEEE Jordan Conference on
Print_ISBN :
978-1-4799-7442-9
DOI :
10.1109/AEECT.2015.7360556