Automated Optimisation of Multi Stage Refrigeration Systems within a Multi-Objective Optimisation Framework

This work demonstrates an automated optimisation of a two stage refrigeration system, which is embedded into an Excel-based Multi-Objective Optimisation (EMOO) framework. The proposed framework has been demonstrated using the Rectisol (TM) process with CO2 capture as an example. The automated optimisation procedure assesses any opportunities to exploit "pockets" in the process Grand Composite Curve (GCC), besides analysing the GCC for two discrete refrigeration temperature levels. The program uses a Co-efficient of Performance (COP) approximation to estimate the required electrical duty. The results of this sub-program are analysed as part of the wider Multi-Objective Optimisation (MOO) which sets the process decision variables such as the solvent flow-rates and solvent regeneration pressure levels in order to minimise the total electrical power consumption and maximise CO2 capture rate. Two options for increasing the pressure of the captured CO2, i.e. by condensation and pumping of CO2 up to 100 bar (Case-I) and by compression up to 100 bar (Case-II) have also been compared by assessing their respective Pareto plots. This is interesting as the condensation case adds an additional refrigeration duty.