An optimization-simulation strategy has been applied by coupling a commercial process simulator (Aspen HYSYS ) with a programming tool (MATLAB ) to produce a precise steady state simulationbased optimization of a whole green-field saturated gas plant as a real case study. The plant has more than 100-components and comprises interacting three-phase fractionation towers, pumps, compressors and exchangers. The literature predominantly uses this coupling to optimize individual units at small scales, while paying more attention to optimizing discrete design decisions. However, bridging the gap to scalable continuous design variables is indispensable for industry. The strategy adopted is a merge between sensitivity analysis and constrained bounding of the variables along with stochastic optimization algorithms from MATLAB such as genetic algorithm (GA) and particle swarm optimization (PSO) techniques. The benefits and shortcomings of each optimization technique have been investigated in terms of defined inputs, performance, and finally the elapsed time for such highly complex case study. | Optimization of a saturated gas plant Meticulous simulation-based optimization A case study
