Heat recovery steam generator (HRSG) is the most important part of the waste heat utilization

and the start-up

shutdown and off-design operation of the HRSG directly determines its life and efficiency. Based on the thermodynamic properties and mass

momentum and energy conservation equations

and taking Matlab/Simulink as the research platform

a dynamic simulation model of the single phase heat transfer surface of HRSG is built in this paper. Combined with the experimental data of the HRSG designed by research group in a cement plant

the parameter optimization of the dynamic model is carried out based on genetic algorithm and particle swarm optimization algorithm. The results show that after optimization

the dynamic model of the waste heat boiler is matched with the experimental data

and the error of the model is 0.93%-4.39%. The dynamic model can be used to simulate the temperature change of the heat transfer surface under different working conditions. And through the comparison of the two algorithms

it shows that particle swarm optimization algorithm has obvious advantages in parameter optimization. The fitness function convergence value is better

and in the convergence iteration

it finishes between the 54 and 64 generation. The genetic algorithm achieves convergence after the 93 generation.