Optimisation of pre-combustion capture for IGCC with a focus on the water balance

Abstract

Abstract Multi-objective optimisation is applied to the simulation of an IGCC power station with solvent based CCS technology. An Aspen Plus ® model of the IGCC power station including CCS is interfaced with an Excel based genetic algorithm to optimise the process. The process is optimised with respect to capital cost and energy efficiency for a range of operating conditions of the solvent plant. This work is based on an air-blown gasification process consuming pre-dried lignite, it uses pinch analysis to design a HRSG for the IGCC power station with CCS to determine the power produced by the power station as well as estimating the additional capital costs due to the CCS equipment. The genetic algorithm then determines a range of non-dominated solutions by systematically adjusting the range of variables studied. Multiple-Objective Optimisation enables the decision makers to see a range of non-dominated options for multiple objectives. This can help to identify an appropriate technology or an operating regime for an individual technology that best suits the projects multiple objectives. In this example the gas temperature into the solvent absorber should be around 130 °C, the regenerator pressure should be around 2 bara and the lean solvent loading between 0.37 and 0.42 to maximise the net power output.