A dynamic model of supercritical boiler-turbine unit based on immune genetic algorithm parameter identification

In recent years, with the development of coal-fired units towards large capacity and high parameters, the position of supercritical once-through boiler unit has become more prominent. In this paper, a nonlinear mathematical model of the supercritical boiler unit is established through a series of assumptions and formula derivation, and then the parameters are identified through regression analysis and immune genetic algorithm (IGA) combined with the operation data of a 1000MW supercritical unit. The inputs of the model are fuel command, feed water and turbine governor valve position while the outputs are turbine power, main steam pressure and steam enthalpy at separator outlet. The simulation results show that the model can characterize the dynamic characteristics of the unit and has acceptable accuracy.