Online Optimization of Fluid Catalytic Cracking Process via a Hybrid Model Based on Simplified Structure-Oriented Lumping and Case-Based Reasoning

Abstract

The mechanism models based on structure-oriented lumping (SOL) deliver a satisfactory prediction on the properties and yield distribution of the products from fluid catalytic cracking (FCC). However, with high complexity and low computing efficiency, such a model is increasingly unable to meet the needs of refineries to produce lighter and greener products using heavier and poorer feedstocks. Therefore, in this paper, a modeling approach hybridizing molecular mechanism and data models was proposed to describe the maximizing iso-paraffins (MIP) technology of the FCC process. This proposed model showed assured prediction accuracy with shortened computing time and thus was appropriate for online application. In this work, model simplification was carried out: less molecules and reactions (3078 and 5216, respectively) were adopted, along with a simplified reactor model, which largely reduced the computation load. CatBoost algorithm was also adopted for constructing a data model, to compensate for the accuracy loss resulting from the simplified SOL mechanism model. Combining with the mechanism model, it ensured the accuracy of prediction while greatly shortened the computing time. Furthermore, to overcome the strong coupling between the process variables to be solved, this work adopted the method of case-based reasoning (CBR) to optimize the process and expanded the case base with the prediction results of the hybrid model, which ensured the feasibility of the solution parameters and shortened the computing time. The hybrid model and the corresponding process optimization strategy proposed were then applied to an industrial FCC MIP process for verification. The results show that the hybrid model could assure the prediction accuracy (comparable with the conventional mechanism model) while the computing time was reduced from more than 20 h to less than 1 min. In the process optimization validation test, the total liquid yield increased by 1.19% on average for 43 out of 50 sets of operating configurations and the coke yield decreased by 1.05% on average. This work provides a good solution for the online process optimization of FCC.

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Flow distribution analysis of a novel fcc system through experiment study and atomic model

“…On the other hand, process optimization, process control [37], and real-time monitoring in every component of the FCC system are very necessary. The model accuracy is very crucial to performing process optimization in the FCC system [38]. Therefore, it requires another technique that could give a lower computational cost.…”

“…Therefore, it requires another technique that could give a lower computational cost. A combination of the model mechanism based on simplified structure-oriented lumping (SOL) and CatBoost machine learning model had been presented [38]. The model can reduce the computational cost from 20 hours to be only a minute with an accurate result.…”