典型变量算法在北班加西燃气轮机发电系统辨识中的应用

O. Mohamed, A. Khalil, Marwan Limhabrash, Jihong Wang
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引用次数: 3

摘要

多年来,燃气轮机的建模和识别一直是一个有趣的研究领域,而且在未来的许多年里还将如此。本文阐述了子空间状态空间系统识别的典型变量算法或典型变量分析(CVA)方法。北班加西电厂(NBPP)正在运行的燃气轮机是本文研究的重点。从数学和线性代数的角度对CVA进行了描述。对所研究的燃气轮机的过程进行了说明和讨论。通过采集所研究电厂的运行数据,利用MATLAB系统识别工具箱建立状态空间模型,并针对不同的数据信号进行了测试。仿真结果表明了该辨识方法的鲁棒性和准确性。
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The application of System Identification via Canonical Variate Algorithm to North Benghazi gas turbine Power generation system
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.
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