SIMPLE MODELING OF REFINING PROCESSAND ON-LINE SIMULATION OF ATMOSPHERIC AND VACUUM DISTILLATION PROCESS BASED ON CAPE-OPEN STANDARD

Abstract

Abstract: Simple refining process model is widely used in operation monitoring, on-line calculation, real-time optimization and other fields. However, most of the models only correlate the input and output variables, so they can not calculate the composition of each group of diverting quantities and can not be integrated into the simulation software to simulate the whole process. In this study,the separation process was simplified,and a simple refinery column model based on CAPE-OPEN standardwas developed. Firstly, the refining process was simplified as a continuous separation unit, and the model parameters could be corrected according to the actual product datato simulate a real process. Secondly, the model parameters were combined with the actual operating variable data, and radial basis interpolation was used to establish the influence of operating variables on the model parameters, so as to realize the simulation of various operating conditions. Finally, three working conditions of commercial atmospheric and vacuum distillation unit were verified. The results showed that compared with Aspen's calculation results, the deviation of the preflash column was mostly within 2%, and the average deviation of the side lines of the atmospheric and vacuum column was less than 3%;compared with the actual results, the average error is less than 5%, in line with the allowable engineering error range. The calculation speed of the model is fast, andthe calculation of each columnis completed in about 0.2 s, which is suitable for on-line production and scheduling.

Key words: simple refining model, process modeling, CAPE-OPEN, online simulation calculation, atmospheric and vacuum distillation unit

References

[1]Chu F, Dai B, Ma X, et al. A Minimum-Cost Modeling Method for Nonlinear Industrial Process Based on Multimodel Migration and Bayesian Model Averaging Method [J]. IEEE Transactions on Automation Science and Engineering, 2019, 17(2): 947-956. [2] 黄德先, 江永亨, 金以慧. 炼油工业过程控制的研究现状、问题与展望[J]. 自动化学报, 2017, 43(6): 902-916. HUANG Dexian, JIANG Yongheng, JIN Yihui. Present research situation, major bottlenecks, and prospect of refinery industry process control[J]. Acta Automatica Sinica, 2017, 43(6): 902-916. [3] 刘广杰, 孙晓岩, 毕荣山, 等. 复杂炼油塔模拟的改进联立方程内外层算法 [J]. 化工学报, 2020, 71(05): 2118-2127. [4] Smith R, Ochoa-Estopier L M, Jobson M. The use of reduced models in the optimisation of energy integrated processes [J]. Chemical Engineering Transactions, 2013, 35: 139-144. [5] Zhao H, Rong G, Feng Y. Effective solution approach for integrated optimization models of refinery production and utility system [J]. Industrial & Engineering Chemistry Research, 2015, 54(37): 9238-9250. [6] Li J, Xiao X, Boukouvala F, et al. Data‐driven mathematical modeling and global optimization framework for entire petrochemical planning operations [J]. AIChE Journal, 2016, 62(9): 3020-3040. [7] Ketabchi E, Mechleri E, Arellano-Garcia H. Increasing operational efficiency through the integration of an oil refinery and an ethylene production plant [J]. Chemical Engineering Research and Design, 2019, 152: 85-94. [8] Mejdell T, Skogestad S. Estimation of distillation compositions from multiple temperature measurements using partial-least-squares regression[J]. Industrial & Engineering Chemistry Research, 1991, 30(12): 2543-2555. [9] Mahalec V, Hashim A, Sanchez Y. Hybrid Models for Monitoring & Optimization of Hydrocarbon Separation Equipment[C]//Proceedings of the 2nd Annual Gas Processing Symposium. Elsevier, 2010: 427-435. [10] BROOKS R W, WALSEM F D V, DRURY J. Choosing cutpoints to optimize product yields[J]. Hydrocarbon Processing, 1999, 78(11): 53-60. [11] ZHANG J, ZHU X X, TOWLER G P. A simultaneous optimization strategy for overall integration in refinery planning[J]. Industrial & Engineering Chemistry Research, 2001, 40(12): 2640-2653. [12] LI Wenkai, HUI Chiwai, LI Anxue. Integrating CDU, FCC and product blending models into refinery planning[J]. Computers & Chemical Engineering, 2005, 29(9): 2010-2028. [13] MENEZES Brenno C, KELLY Jeffrey D, GROSSMANN Ignacio E. Improved swing-cut modeling for planning and scheduling of oil-refinery distillation units[J]. Industrial & Engineering Chemistry Research, 2013, 52(51): 18324-18333. [14] ALATTAS Abdulrahman M, GROSSMANN Ignacio E, PALOU-RIVERA Ignasi. Integration of nonlinear crude distillation unit models in refinery planning optimization[J]. Industrial & Engineering Chemistry Research, 2011, 50(11): 6860-6870. [15] Lee D H, Lee E S, Park S J. Characterization of crude feed and products from operating conditions by using continuous probability functions and inferential models[J]. Korean Journal of Chemical Engineering, 2006, 23(4): 517-521. [16] Yao H, Chu J. Operational optimization of a simulated atmospheric distillation column using support vector regression models and information analysis [J]. Chemical Engineering Research and Design, 2012, 90(12): 2247-2261. [17] Ochoa-Estopier L M, Jobson M, Smith R. Operational optimization of crude oil distillation systems using artificial neural networks [J]. Computers & Chemical Engineering, 2013, 59: 178-185. [18] Mahalec V, Sanchez Y. Inferential monitoring and optimization of crude separation units via hybrid models [J]. Computers & Chemical Engineering, 2012, 45: 15-26. [19] Fu G, Sanchez Y, Mahalec V. Hybrid model for optimization of crude oil distillation units [J]. AIChE Journal, 2016, 62(4): 1065-1078. [20] Li F, Qian F, Yang M, et al. Product tri‐section based crude distillation unit model for refinery production planning and refinery optimization [J]. AIChE Journal, 2021, 67(2): e17115. [21] 周磊, 孙晓岩, 陶少辉, 等. 基于分离因数法的简捷炼油塔模型开发及应用 [J/OL]. 化工进展: 1-12. [22] Gutmann H-M. A radial basis function method for global optimization [J]. Journal of Global Optimization, 2001, 19(3): 201-227. [23] Gutmann H-M. On the semi-norm of radial basis function interpolants [J]. Journal of Approximation Theory, 2001, 111(2): 315-328. [24] Soares R d P, Secchi A R. EMSO: A new environment for modelling, simulation and optimisation [M]. Computer Aided Chemical Engineering. Elsevier. 2003: 947-952. [25] Van Baten J, Szczepanski R. A thermodynamic equilibrium reactor model as a CAPE-OPEN unit operation [J]. Computers & Chemical Engineering, 2011, 35(7): 1251-1256. [26] 李旭, 马力. VB6在CSV文件格式处理中的应用研究 [J]. 信息技术, 2009, 33(07): 26-28.