Modeling And Parameter Identification For Supercritical Steam Turbine And Governor

Test and adjust system parameters turbine and generator, excitation system, power load model together make up the "four parameter test", and is the generator and network security assessment is an important task. Steam turbine system is the adaptive parameter identification optimization control, status monitoring and fault diagnosis system is one important means.Supercritical steam turbine and its current governor system parameter identification and modeling of the current status of research and analysis to study the parameter identification methods, parameter calculation method and system modeling. Using the modular modeling method for steam turbine speed control system aspects of mathematical modeling; turbine and control system design parameters of the test trials, collecting field data; of steam turbine speed control system parameter identification and its method of calculating the least squares algorithm to choose the applicable parameter identification, and checking identification results were compared, and ultimately arrive at an accurate identification parameters; the results of parameter identification and model simulation.On-site measurement data for steam turbine governor system model and parameter identification is a very cumbersome and complex process of data preprocessing and recognition of work-related parameters is quite large, it is necessary for data processing and parameter identification software development. Matlab is the world’s scientific computing and control engineering in the field of relatively mature application, the window of their own graphical design platform MatlabGuide able to use the Matlab toolbox functions to prepare plans visualization applications, and can be compiled into stand-alone application executable software. Using Matlab and the speed control system for steam turbine map visualization software was written, the software functionality, including data loading, data capture, data to noise, per unit of data, data normalization, the model parameter identification, model simulation and parameter output and so on.