The complexity of lipid feedstocks and the lack of data on physical
properties hinder the simulation of oleochemical processing units. In
this work, an iterative lumping approach is proposed to define an
adequate number of key components such that diversification between
lipid feedstocks becomes possible, while keeping the determination of
physical properties as required for process modelling manageable. As a
case study, the iterative lumping approach is used for simulation and
optimization of a fatty acid distillation plant. For predicting
vapour-liquid equilibria of fatty acids, the best results were acquired
using the property method UNIQ-HOC. Using the iterative lumping
approach, 11 key components were selected to represent the feedstock.
The process model properly predicts the product composition, yield,
purity and heat duty. The most important process parameters are found to
be side-reflux-ratio, reboiler-outlet-temperature and heat-duty of the
pitch-distiller. For optimization, an increase of the side-reflux-ratio
and reboiler-outlet-temperature, is recommended.