Abstract
Petroleum is an indispensable and important fuel for the development of modern industry, as well as an indispensable basic source of organic chemical raw materials and transportation fuels. However, the composition of petroleum is extremely complex and can only be fully utilized after proper separation. According to the different processes, the oil processing technology can be divided into primary processing and secondary processing. Among them, secondary processing refers to other processing processes using crude oil distillation products as raw materials, including catalytic cracking (FCC) and hydrocracking (HC). However, in today’s society, businesses face major challenges due to issues such as pollution and energy crisis. For example, low energy consumption and excessive pollutant emissions have resulted in a great waste of resources, while high environmental policy costs have caused many economic burdens. Minimizing costs and improving economic benefits have become the goals of modern enterprise management. At the same time, particle swarm optimization, as a calculation method with strong global search ability and fast convergence speed, can provide a new way of thinking for model optimization, and has been widely used in practical production and life. In this paper, the experimental analysis method and data analysis method are used to better understand the results of multi-objective optimization of FCC separation system through experiments. According to the experimental results, the recirculation flow rates in the main fractionation tower were 23100, 38710, 34900, and 42410 kg/h, respectively. It can be seen that the energy consumption is effectively reduced and the yield is improved. The above results can provide an important reference for the design and optimization of the FCC separation system.
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Acknowledgement
Project name 2: Henan Normal University 18 Doctor Start-up Project Funding (project code: 5101119170147);
Project name 3: The 2017 Youth Science Foundation Project of Henan Normal University (Project Code: 5101119170305);
Laboratory: Engineering Lab of Intelligence Business & Internet of Things, Henan Province.
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Wang, S. (2023). Multi-objective Optimization of FCC Separation System Based on Particle Swarm Optimization. In: Abawajy, J.H., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) Tenth International Conference on Applications and Techniques in Cyber Intelligence (ICATCI 2022). ICATCI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-031-28893-7_3
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DOI: https://doi.org/10.1007/978-3-031-28893-7_3
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