Multi-objective optimisation of CCs using simulation, heat integration and cost estimation
2017-02-17T01:12:46Z (GMT) by
Carbon capture and storage (CCS) using solvent based absorption has the potential to significantly reduce the carbon intensity of power stations. It is one of a range of technologies that is necessary to be deployed in able to reduce greenhouse gas emissions at the lowest cost. However, the addition of CCS to power stations will increase the capital and operating expenditure of the power station and will reduce the net power produced from the power station. Therefore, minimising both the capital cost and the energy penalty associated with CCS will be imperative to ensuring that the cost of electricity of power stations with CCS remains competitive. This research uses multi-objective optimisation (MOO) of the CCS system applied to pulverised coal power stations using a combination of process simulation, heat integration using a linear programming form of pinch analysis and cost estimation. The benefit of combining MOO with automated pinch analysis is that the heat exchanger network does not need to be defined for the optimisation of the process synthesis. In this project, heat integration has shown to potentially lead to significant reductions in the energy penalty associated with the addition of CCS. Capturing 90 % of the CO2 in the flue gas, the energy penalty can be reduced from 38 % without heat integration, to just 14 % with a fully optimised and heat integrated solvent system. However, when the capital and operating costs are factored into the optimisation, to minimise the differential cost of electricity, the optimum level of heat integration may be more moderate, with energy penalties of between 25 and 30 %.