Because of the large scale feature of the rigorous model

process optimization on multi-stage columns could be difficult to converge.In this paper

a reduced-order model based on the group method is proposed for high purity distillation columns which correlates the component recoveries with absorption factors and number of theoretical stages.Considering the strongly nonlinear characteristics of absorption factor along the column of high purity distillation column

a piecewise linear fitting method is proposed to obtain the component recoveries.Simulations are conducted under different loads to compare the performance of the reduced-order model and the rigorous model.The results show that the model scale is dramatically decreased from 2377 variables in the rigorous model to 34 variables in the proposed reduced-order model

the convergence time is also greatly reduced from 6136 s to that around 1 s

but the model accuracy is not damaged with very small errors between these two models.