Simultaneous Optimization and Heat Integration Based on Rigorous Process Simulations

Abstract

Abstract This paper introduces a novel simultaneous optimization and heat integration approach, which can be used directly with the rigorous models in process simulators. The approach is based on the formulation of Papoulias and Grossmann (1983), in which heat integration is formulated as a LP transshipment model and solved simultaneously during optimization of the flowsheet. In this case, the overall process is optimized utilizing external derivative free optimizers (DFOs), which interact directly with the process simulation. Heating and cooling loads are transferred to the heat integration module and solved for each iteration of the DFO to update the minimum utility targets. The heat integration subproblem is solved via calls to GAMS. This approach has been implemented and demonstrated within the Carbon Capture Simulation Initiative’s Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS). This paper describes the automated heat integration capabilities and demonstrates its application for integrating a post-combustion carbon capture and compression system with a supercritical pulverized coal power plant. The case study results indicate that this simultaneous approach is relatively easy to implement and achieves higher net power plant efficiency than the sequential approach.