Minimization of water consumption under uncertainty for PC process

Integrated gasification combined cycle (IGCC) technology is becoming increasingly important for the development of advanced power generation systems. As an emerging technology different process configurations have been heuristically proposed for IGCC processes. One of these schemes combines water-gas shift reaction and chemical-looping combustion for the CO2 removal prior the fuel gas is fed to the gas turbine reducing its size (improving economic performance) and producing sequestration-ready CO2 (improving its cleanness potential). However, these schemes have not been energetically integrated and process synthesis techniques can be used to obtain optimal flowsheets and designs. This work studies the heat exchange network synthesis (HENS) for the water-gas shift reaction train employing a set of alternative designs provided by Aspen energy analyzer (AEA) and combined in a process superstructure that was simulated in Aspen Plus (AP). For the alternative designs, large differences in the performance parameters (for instance, the utility requirements) predictions from AEA and AP were observed, suggesting the necessity of solving the HENS problem within the AP simulation environment and avoiding the AEA simplifications. A CAPE-OPEN compliant capability which makes use of a MINLP algorithm for sequential modular simulators was employed to obtain a heat exchange network that provided a cost of energy that was 27% lower than the base case.