Simulation and Optimization of Gas Sweetening Plant of Iraq Majnoon Refinery

Document Type : Original Article

Authors

1 Faculty of Chemical Engineering, University of Mazandaran, Babolsar, Iran

2 Faculty of Electrical Engineering, University of Mazandaran, Babolsar, Iran

Abstract

In this research, gas sweetening process of the Iraq Majnoon refinery plant and its optimization scenarios were investigated using ASPEN HYSYS 8.4 and genetic algorithm optimization. First, values of optimization parameters such as the values of the population, generations and crossover for single and multi-objective optimizations were obtained. The effect of temperature and molar flow of feed gas and make-up water on concentration of CO2 and H2S in the sweet gas were studied. The result showed that with increasing the temperature and molar flow of feed gas, the concentration of CO2 and H2S in the sweet gas was increased. The single and multi-objectives’ optimizations of process were carried out with minimizing the concentration of CO2 and H2S, minimizing the consumed energy of stripper and overall consumed energy of plant including energy of stripper and cooler. It was observed that for optimization of concentration of CO2 and H2S, mole fraction of CO2 and H2S decreased to minimum amounts of 5.52 e-4 and 6.84 e-9 between optimization data sets. Also, it was found that with increasing the number of objective functions of the optimization, the ability of the algorithm to reduce the amount of the objective functions decreases, because genetic algorithm should consider more constraints with increasing the number of objective functions. The novelty of this research was a comprehensive study of gas sweetening process optimization with single to four objectives.

Keywords

Main Subjects

References

  1. Ellaf, A., Taqvi, S. A. A., Zaeem, D., Siddiqui, F. U. H., Kazmi, B., Idris, A., Alshgari, R. A. and Mushab, M. S. S., 2023. Energy, exergy, economic, environment, exergo-environment based assessment of amine-based hybrid solvents for natural gas sweetening, Chemosphere, 313, pp. 137426. Doi:10.1016/j.chemosphere.2022.137426
  2. Tikadar, D., Gujarathi, A. M. and Guria, C., 2021. Safety, economics, environment and energy based criteria towards multi-objective optimization of natural gas sweetening process: an industrial case study, Journal of Natural Gas Science and Engineering, 95, pp. 104207. Doi:10.1016/j.jngse.2021.104207
  3. Zare Aliabad, H. and Mirzaei, S., 2009. Removal of CO2 and H2S using aqueous alkanolamine solutions, World Academy of Science, Engineering and Technology, 49(1), pp. 194-203. Available at: https://www.academia.edu/download/50764935/Removal-of-CO2-and-H2S-using-Aqueous-Alkanolamine-Solusions_1.pdf
  4. Gudmundsson, J. S., Nazir, A., Ismailpour, A., Saleem, F., Idrees, M. U. and Zaidy, S. A. H., 2013. Natural gas sweetening & effect of declining pressure, TPG4140 Project Report; NTNU: Trondheim, Norway. Available at: https://www.academia.edu/download/33632789/10Nazir.pdf
  5. Pellegrini, L. A., Moioli, S., Picutti, B., Vergani, P. and Gamba, S., 2011. Design of an acidic natural gas purification plant by means of a process simulator, Chemical Engineering Transactions, 24, pp. 271-276. Available at: https://folk.ntnu.no/skoge/prost/proceedings/pres2011-and-icheap10/ICheaP10/412Pellegrini.pdf
  6. Abdulrahman, R. and Sebastine, I., 2013. Natural gas sweetening process simulation and optimization: A case study of Khurmala field in Iraqi Kurdistan region, Journal of Natural Gas Science and Engineering, 14, pp. 116-120. Doi:10.1016/j.jngse.2013.06.005
  7. Berrouk, A. S. and Ochieng, R., 2014. Improved performance of the natural-gas-sweetening Benfield-HiPure process using process simulation, Fuel Processing Technology, 127, pp. 20-25. Doi:10.1016/j.fuproc.2014.06.012
  8. Qeshta, H. J., Abuyahya, S., Pal, P. and Banat, F., 2015. Sweetening liquefied petroleum gas (LPG): Parametric sensitivity analysis using Aspen HYSYS, Journal of Natural Gas Science and Engineering, 26, pp. 1011-1017. Doi:10.1016/j.jngse.2015.08.004
  9. Kazemi, A., Malayeri, M. and Shariati, A., 2014. Feasibility study, simulation and economical evaluation of natural gas sweetening processes–Part 1: A case study on a low capacity plant in iran, Journal of Natural Gas Science and Engineering, 20, pp. 16-22. Doi:10.1016/j.jngse.2014.06.001
  10. Fouad, W. A. and Berrouk, A. S., 2013. Using mixed tertiary amines for gas sweetening energy requirement reduction, Journal of Natural Gas Science and Engineering, 11, pp. 12-17. Doi:10.1016/j.jngse.2012.07.003
  11. Al-Lagtah, N. M., Al-Habsi, S. and Onaizi, S. A., 2015. Optimization and performance improvement of Lekhwair natural gas sweetening plant using Aspen HYSYS, Journal of Natural Gas Science and Engineering, 26, pp. 367-381. Doi:10.1016/j.jngse.2015.06.030
  12. Muhammad, A. and GadelHak, Y., 2015. Simulation based improvement techniques for acid gases sweetening by chemical absorption: A review, International Journal of Greenhouse Gas Control, 37, pp. 481-491. Doi:10.1016/j.ijggc.2015.03.014
  13. Gutierrez, J. P., Benitez, L. A., Ruiz, E. L. A. and Erdmann, E., 2016. A sensitivity analysis and a comparison of two simulators performance for the process of natural gas sweetening, Journal of Natural Gas Science and Engineering, 31, pp. 800-807. Doi:10.1016/j.jngse.2016.04.015
  14. Akinola, T. E., Oko, E. and Wang, M., 2019. Study of CO2 removal in natural gas process using mixture of ionic liquid and MEA through process simulation, Fuel, 236, pp. 135-146. Doi:10.1016/j.fuel.2018.08.152
  15. Jagannath, A. and Almansoori, A., 2018.Process Synthesis and Simulation of Amine Solvent Regeneration in Natural Gas Sweetening Units Using Heat Pump Assisted Configurations, Abu Dhabi International Petroleum Exhibition and Conference: Society of Petroleum Engineers (SPE), pp. D042S207R002. Doi: /10.2118/192745-MS
  16. Alnili, F., James, P. and Barifcani, A., 2019. Natural gas sweetening using low temperature distillation: simulation and configuration, Separation Science and Technology, pp. 1-8. Doi:10.1080/01496395.2019.1599018
  17. Azeez, S., Garba, U. and Danshehu, B., 2020. Application of Aspen HYSYS for Predicting the Effects of Impurities on Thermodynamic Performance of Glycerol Autothermal Reforming for Hydrogen Production, Iranian (Iranica) Journal of Energy & Environment, 11(1), pp. 51-56. Doi:10.5829/ijee.2020.11.01.08
  18. Holland, J. H., 1992. Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press. 0262581116.
  19. Jamiati, M., 2021. Modeling of Maximum Solar Power Tracking by Genetic Algorithm Method, Iranian (Iranica) Journal of Energy & Environment, 12(2), pp. 118-124. Doi: 10.5829/ijee.2021.12.02.03
Iranica Journal of Energy & Environment
Volume 15, Issue 1
January 2024
Pages 21-37

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