A method for HTL biocrude simulation using multi-objective optimisation and fractional distillation

Abstract

A novel approach for modelling hydrothermal liquefaction (HTL) biocrude is presented, using a combination of fractional distillation data of biocrude and multi-objective optimisation to simulate the biocrude various properties using the non-dominated sorting genetic algorithm (NSGA-II). The complex composition of biocrude has made it challenging to analyse and simulate in process models. Most HTL simulation studies use a simple basis for biocrude using limited GC–MS data, which may not be reliably accurate. Applying multi-objective optimisation reduced the density and TBP curve error by ten times compared to single-objective optimisation. In addition,the results were further improved by combining distillation experimental data into multi-objective optimisation, in contrast with previous studies which used only the biocrude data. Separating complicated HTL biocrude into five fractions and analysing the obtained results increased the number of candidate databank compounds from 72 to 216, which led to a noticeable improvement in the accuracy of the model.