Modeling of Reheated Steam Temperature System using a Generalized Regression Neural Network

نویسندگان

  • Soonyoung Lee
  • Li Yun-Peng
چکیده

In order to control the power plant accurately, exact models of the reheater and attemperator are needed. But sometimes due to a lack of needful information and complex internal structure of the system, it is unadvisable to establish the dynamics model based on energy mass balance, physical rules and thermodynamics principles. In this paper, a generalized regression neural network(GRNN) is developed to identify the thermodynamic system of reheater and attemperator. The models of the reheater and the attemperator are derived by using the GRNN and trained by using Matlab neural network toolbox. These models are developed for a once-though type boiler based on the real data obtained in 500[MW] power plant. The responses of the proposed models are well matched with the outputs of the real plant.

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تاریخ انتشار 2013