Data-driven robust optimization for cyclic scheduling of ethylene cracking furnace system under uncertainty based on kernel learning

Lin, Xinwei; Zhao, Liang; Chen, Shang; He, Wangli; Du, Wenli; Qian, Feng

doi:10.1016/j.ces.2022.117919

Cited by 3 publications

(1 citation statement)

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“…In addition, circulating water and industrial water are used for heat exchange and circulation in the production process . In brief, ethylene production processes include the cracking, cooling, compression, and quench sectors . Feed stocks are converted to final product ethylene and byproducts through the sequence procedure.…”

Section: Introductionmentioning

confidence: 99%

Integrated Modeling and Optimization for Ethylene Production Processes Coupled with the Utility System

Ma,

Zhao,

Yang

2024

Ind. Eng. Chem. Res.

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Ethylene production is primarily concerned with improving economic benefits. Modeling and optimization of ethylene production processes are challenging due to their complexity and coupling with the utility system. In existing approaches, utility system interactions are not considered, which could result in suboptimal solutions. This paper presents a new modeling and optimization framework for integrating production processes with utility systems by recovering superhigh-pressure steam from the cracking process. A data-driven model based on industrial and software-generated data is used in conjunction with an existing mechanism model for simplifying complex process engineering and reducing the optimization difficulty. The case study shows that this methodology increases the profit by 5%. Sensitivity analysis confirms sufficient stability to withstand market fluctuations.

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Section: Introductionmentioning

confidence: 99%