Recently, exergy analysis has attracted great attention of the scientific community as an attractive tool for evaluating energetic efficiency of any process. In this work, the simulation of the amine treatment unit in a Latin-American refinery was performed in order to apply the exergy analysis tool to identify alternatives of improvement. The industrial amine treatment unit was simulated using Aspen plus software, which provided extended energy and mass balances. To calculate irreversibilities of the process and global exergy efficiencies per stages, the general methodological procedure of exergy analysis was used. To this end, physical and chemical exergies were found for compounds involved within the process. The values estimated for total irreversibilities, exergy of utilities, and exergy of wastes in the treatment of the sulfur-rich amine allowed us to analyze the stages that require reductions in waste generation and utility consumption. For a processing capacity of 72.08 t/h of rich amine, results revealed that the overall exergy efficiency was 83.81% and the total irreversibility was 1.69 × 105 MJ/h, where 23.6% corresponds to the total exergy by residues (3.98 × 104 MJ/h). The novel strategy to use exergy analysis for process optimization proved to be useful to detect critical stages and prioritize actions to improve.
In this work, the mercaptan oxidation unit of an oil and gas refinery was simulated and assessed using exergy and parametric sensitivity analysis to identify opportunities for improvement from a technical and energy point of view. The process simulation was performed using Aspen HYSYS V10.1 to obtain extended mass and energy balances. The simulation results were validated with the data available in the literature. The effects of operating conditions on technical performance were analyzed via parametric analysis. The exergy analysis was applied to two case studies: the base case and the resulting case from technical improvements. The global exergy efficiency, irreversibilities, exergy of utilities, and efficiencies per stage were calculated to map process equipment with the highest losses of exergy. A comparison between both base and alternative cases was introduced in order to analyze increments in exergy efficiencies. An exergy efficiency of 84.21% was found for the base case, while for the alternative case after applying parametric sensitivity, it was calculated to be 81.95%. This decrease by 2.26% was attributed to the increase of irreversibilities and exergy of wastes to achieve a product with better quality standards.
In this work, a sour water treatment unit was evaluated combining exergetic analysis and parametric sensitivity analysis. Process simulation was performed using Aspen HYSYS 10.1 following real refinery configurations, and the results were validated with existing data. The parametric sensitivity was evaluated by varying the effect of process variables to identify an alternative case with the best technical performance. The exergy analysis was applied to both base and alternative cases. The outcomes were exergy efficiency by stages, global exergy efficiency, total irreversibilities, and exergy by industrial services. A comparison of both cases was performed to identify opportunities for improvement in real sour water treatment. Results revealed that the overall exergy efficiency for the base case was 44.28%. After improving the technical performance, the overall exergy efficiency decreased to 36.12%; the latter indicated higher irreversibilities due to the increase in the use of industrial services. This finding suggested that those process improvements may affect the performance of this refinery unit from an exergetic point of view.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.