Directing against the MISO dynamic model of superheater for ultra-supercritical units

a model parameter identification method based on genetic algorithm(GA) has been put forward.The genetic operators have been improved as displacement sequence with ensuring quality selection

non-uniform linear crossover

and Gaussian mutation

the uniform design method is used to construct the initial sort group.The adaptability of Sigmoid function is used to adjust the probabilities of crossover and mutation

so as to enhance the convergence precision and operational speed of GA.The result of parameter identification emulation for operation data of ultra-supercritical unit in Haimen Power Plant shows that the improved GA method boasts better operational performance

the predicted output variation tallies basically with the actual variation of main steam temperature

can reflect the dynamic properties of high temperature superheater.