Multi-Objective Optimization of Kinetic Characteristics for the LBPRM-EHSPCS System

Zhang, Yuhang; Chen, Gexin; Yan, Guishan; Li, Boyuan; Lu, Jianxin; Jiang, Wenguang

doi:10.3390/pr11092623

Cited by 1 publication

(1 citation statement)

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“…In chemical processes, there commonly exist multi-rate systems [4][5][6]. It is passively generated due to the process constraints of production, safety, economy, or environment, and on the other hand, it is artificially constructed due to the need for process control [7][8][9]. The multi-rate problem mainly exists for the following reasons: (1) the implementation of dynamic optimization is limited by operation rate [10][11][12]; (2) in the actual process, the number of sensors is less than the number of output variables, so time-sharing measurement is adopted [13][14][15]; (3) in the chemical process, the change frequency for each optimization variable may greatly differ from others; (4) in addition to the multirate phenomenon in the actual process, some operation optimizations require multi-rate operation [16][17][18], such as pole assignment, enhanced dynamic performance, and model following [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Online Dynamic Optimization of Multi-Rate Processes with the Case of a Fluid Catalytic Cracking Unit

Zhang,

Lin,

et al. 2023

Processes

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Due to operational limitations in the industrial field, the operating variables of fluid catalytic cracking units (FCCU) are of multiple operating frequencies, which are CO combustion promoter amount, recycle slurry flow rate, combustion air flow rate, heat escape, and reaction temperature, from low frequency to high frequency. There are usually two schemes for operation optimization of FCCU. The former is called single-rate, single-window optimization, whose operating variables are optimized only once in the whole operation cycle, which is easy to achieve, but the optimization effect is poor. The latter is called single-rate multi-window optimization, whose operating variables are optimized repeatedly and whose operation cycle is discretized into multiple optimization periods with the same frequency, which costs a heavy calculation burden and cannot adapt to the optimization variables with multiple operating frequencies. So, a multi-rate, variable-window online dynamic optimization method is proposed. In an operation cycle, the high-frequency operating variable is optimized in a short optimization period, and the low-frequency operating variable is optimized in a long optimization period; each optimization period has integer multiples to the minimum optimization period. Each optimized result for each optimization period is put into use online immediately. The optimization model involves the time domain differential equations, integral cost objective function, and measured disturbances. The experimental results show that compared with the single-rate, single-window optimization method and single-rate multi-window optimization method, the optimization effect of multi-rate, variable-window online dynamic optimization is better than single-rate, single-window optimization but worse than single-rate multi-window optimization. However, the optimization results are consistent with the operation frequency of each optimization variable, which can be implemented in complex chemical processes and increase certain economic benefits.

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