modeling and optimization of fixed-bed fischer-tropsch synthesis using genetic algorithm

in this paper, modeling and optimization of fischer-tropsch synthesis is considered in a fixed-bed catalytic reactor using an industrial fe-cu-k catalyst. a one dimensional pseudo-homogenous plug flow model without axial dispersion is developed for converting syngas to heavy hydrocarbons. the effects of temperature, pressure, h2 to co ratio in feed stream, and co molar flow on the mass flow rate of the desired product (c5+) are investigated. since the fischer-tropsch synthesis produces a wide range of hydrocarbon products, it is important to optimize the reactor operating parameters and feed conditions to maximize yield of reactor. genetic algorithm was used as the optimization algorithm in this study. the processing variables are defined in the following ranges: temperature: 493-542 k, pressure: 10.9-30.9 bar, co molar flow: 0.0815-0.3074 gmole/s and the h2/co feed ratio: 0.98-2.99. a reactor model was developed and along with appropriate reaction kinetics, the performance of the reactor was investigated. model results were in good agreement with experimental data. after validating the model, the production of c5+ was optimized. the results indicated that the production of c5+ increased with increasing pressure while it decreased with increasing temperature, h2/co ratio, and co molar flow rate in the feed stream.