Hydrogen sulfide exists mostly as a detrimental byproduct in the gas processing units as well as refineries, and it must be eliminated from natural gas streams. In a Sulfur Recovery Unit (SRU), hydrogen sulfide is converted into the elemental sulfur during the modified Claus process. Efficiency of sulfur recovery units significantly depends on the reaction furnace temperature. In this work, the effect of oxygen and acid gas enrichment on the reaction furnace temperature and accordingly on sulfur recovery is studied, using both numerical modeling and process simulation. Then, simulation and numerical model are benchmarked against the experimental data of an SRU unit. The validated model provides spotlight on optimizing the upstream sulfur removal unit as well as the oxygen purification process. Two cases of acid gas streams with low and high H2S content, 30% and 50%, are studied to investigate the effect of operating parameters on the overall recovery. Finally, average errors of the models are presented. According to the absolute difference with experimental values, the developed numerical model shows great potential for accurately estimating overall efficiency of the recovery unit.
An innovative approach for optimization of the hydrogen network in a refinery is presented. The optimization problem was formulated as a fuzzy-based multiobjective nonlinear programming (FMONLP), aiming at simultaneous minimization of the total annual cost and CO 2 emission. This is achieved by defining an objective function with a weighted sum of the annual cost and CO 2 emission. The weighting factors are considered as fuzzy parameters which are described based on the experts' experiences. The applicability of the proposed approach is illustrated by optimization of an Iranian refinery hydrogen network.
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