A research on superheater mechanism model of intelligent optimization based on spot data

In order to solve the problems of strong coupling and nonlinear parameters of superheater model, in this paper, we aimed at a 600MW subcritical drum boiler high temperature superheater as the object of study .On the basis of mechanism analysis and its dynamic characteristics I built a dynamic model of high superheater contains 9 typical working conditions .I optimized the model parameters by using field data. A continuous nonlinear model is obtained by curve fitting. The simulation results show that superheater model built by this method can better simulate the field characteristic. This model provides a reference design of automatic control system of main steam temperature .This paper aims to provide the basis for the application of advanced control algorithms in the field. Furthermore, this model can provide higher accuracy for on-site training to improve training effect.