CIESC Journal ›› 2022, Vol. 73 ›› Issue (4): 1623-1630.DOI: 10.11949/0438-1157.20211737
• Process system engineering • Previous Articles Next Articles
Biao HAN(),Chao SHANG,Yongheng JIANG,Dexian HUANG()
Received:
2021-12-06
Revised:
2022-01-21
Online:
2022-04-25
Published:
2022-04-05
Contact:
Dexian HUANG
通讯作者:
黄德先
作者简介:
韩彪(1994—),男,博士研究生,基金资助:
CLC Number:
Biao HAN, Chao SHANG, Yongheng JIANG, Dexian HUANG. Object-oriented refinery plant-wide scheduling optimization model and program framework[J]. CIESC Journal, 2022, 73(4): 1623-1630.
韩彪, 尚超, 江永亨, 黄德先. 面向对象的炼油厂全厂调度优化模型及程序框架[J]. 化工学报, 2022, 73(4): 1623-1630.
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订单 | 交货 时刻 | 柴油/吨 | 汽油/吨 | ||||||
---|---|---|---|---|---|---|---|---|---|
GⅢ0# | GⅢ10# | GⅣ0# | GⅢ90# | GⅢ93# | GⅢ97# | JⅣ93# | JⅣ97# | ||
l1 | 16 h末 | 600 | 660 | 368 | 0 | 0 | 0 | 50 | 0 |
l2 | 32 h末 | 200 | 300 | 350 | 200 | 450 | 400 | 170 | 130 |
l3 | 60 h末 | 0 | 0 | 0 | 0 | 354 | 611 | 786 | 400 |
Table 1 Order demand information of the case
订单 | 交货 时刻 | 柴油/吨 | 汽油/吨 | ||||||
---|---|---|---|---|---|---|---|---|---|
GⅢ0# | GⅢ10# | GⅣ0# | GⅢ90# | GⅢ93# | GⅢ97# | JⅣ93# | JⅣ97# | ||
l1 | 16 h末 | 600 | 660 | 368 | 0 | 0 | 0 | 50 | 0 |
l2 | 32 h末 | 200 | 300 | 350 | 200 | 450 | 400 | 170 | 130 |
l3 | 60 h末 | 0 | 0 | 0 | 0 | 354 | 611 | 786 | 400 |
1 | 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 D X, Jiang Y H, Jin Y H. Present research situation, major bottlenecks, and prospect of refinery industry process control[J]. Acta Automatica Sinica, 2017, 43(6): 902-916. | |
2 | 邢勐. 炼油工业过程的控制和研究[J]. 当代化工研究, 2021(20): 24-25. |
Xing M. Process control and research in oil refining industry[J]. Modern Chemical Research, 2021(20): 24-25. | |
3 | 侯芙生. 中国炼油技术[M]. 3版. 北京: 中国石化出版社, 2011. |
Hou F S. Chinese Oil Refining Technology[M]. 3rd ed. Beijing: China Petrochemical Press, 2011. | |
4 | 李莉, 白雪松. 我国炼油行业发展及成品油质量升级建议[J]. 化学工业, 2016, 34(5): 15-20. |
Li L, Bai X S. The suggestion of the product quality upgrading for the development of China's refinery industry[J]. Chemical Industry, 2016, 34(5): 15-20. | |
5 | 刘晓宇, 傅军, 邹劲松, 等. 未来中国炼油技术预见探究[J]. 当代石油石化, 2021, 29(10): 1-9. |
Liu X Y, Fu J, Zou J S, et al. Research on the foresight of future Chinese refining technology[J]. Petroleum & Petrochemical Today, 2021, 29(10): 1-9. | |
6 | 刘初春, 杨维军, 孙琦. 中国炼油行业碳减排路径思考[J]. 国际石油经济, 2021, 29(8): 8-13. |
Liu C C, Yang W J, Sun Q. Thinking on carbon emission reduction path of China's refining industry[J]. International Petroleum Economics, 2021, 29(8): 8-13. | |
7 | 曹湘洪. 能源转型中我国炼油工业面临的挑战与对策[J]. 石油炼制与化工, 2021, 52(10): 1-9. |
Cao X H. Challenges and countermeasures of China's oil refining industry in transformation of energy utilization[J]. Petroleum Processing and Petrochemicals, 2021, 52(10): 1-9. | |
8 | 丁进良, 杨翠娥, 陈远东, 等. 复杂工业过程智能优化决策系统的现状与展望[J]. 自动化学报, 2018, 44(11): 1931-1943. |
Ding J L, Yang C E, Chen Y D, et al. Research progress and prospects of intelligent optimization decision making in complex industrial process[J]. Acta Automatica Sinica, 2018, 44(11): 1931-1943. | |
9 | 陈远东, 丁进良. 炼油生产调度研究现状与挑战[J/OL]. 控制与决策. [2021-12-16]. . |
Chen Y D, Ding J L. Stateofarts and challenges on production scheduling of refinery[J/OL]. 控制与决策. [2021-12-16]. . | |
10 | 柯晓明, 乞孟迪, 吕晓东, 等. “双碳”目标下中国炼化行业“十四五”发展新特点分析与展望[J]. 国际石油经济, 2021, 29(5): 33-38. |
Ke X M, Qi M D, Lyu X D, et al. Analysis of the new features and prospect on the 14th Five-Year Plan development of China's refinery and chemical industry under the “dual carbon” goal[J]. International Petroleum Economics, 2021, 29(5): 33-38. | |
11 | 王浩俨. 炼油化工企业生产调度系统优化的方式方法[J]. 化工管理, 2021(11): 114-115. |
Wang H Y. Optimization method of production scheduling system in refinery and chemical enterprises[J]. Chemical Enterprise Management, 2021(11): 114-115. | |
12 | Joly M, Odloak D, Miyake M, et al. Refinery production scheduling toward Industry 4.0[J]. Frontiers of Engineering Management, 2018, 5(2): 202-213. |
13 | Li M. Multi-periodic refinery scheduling based on generalized disjunctive programming[J]. Journal of Physics: Conference Series, 2020, 1575(1): 012195. |
14 | Wu N Q, Li Z W, Qu T. Energy efficiency optimization in scheduling crude oil operations of refinery based on linear programming[J]. Journal of Cleaner Production, 2017, 166: 49-57. |
15 | Yu L, Wang S J, Xu Q. Optimal scheduling for simultaneous refinery manufacturing and multi oil-product pipeline distribution[J]. Computers & Chemical Engineering, 2022, 157: 107613. |
16 | Xu J L, Qu H L, Wang S J, et al. A new proactive scheduling methodology for front-end crude oil and refinery operations under uncertainty of shipping delay[J]. Industrial & Engineering Chemistry Research, 2017, 56(28): 8041-8053. |
17 | Pereira C S, Dias D M, Vellasco M M B R, et al. Crude oil refinery scheduling: addressing a real-world multiobjective problem through genetic programming and dominance-based approaches[C]//GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York, USA: Association for Computing Machinery, 2018: 1821-1828. |
18 | Chen Y D, Ding J L. Discrete-time scheduling model of entire refinery with multiscale operation time[C]//2021 3rd International Conference on Industrial Artificial Intelligence (IAI). Shenyang, China: IEEE, 2021: 1-6. |
19 | Duan Q Q. An MILP-NLP decomposition approach applied to a refinery scheduling problem[C]//2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion. Macao, China, 2020: 411-417. |
20 | Chen Y D, Ding J L, Chai T Y. A knowledge transfer based scheduling algorithm for large-scale refinery production[J]. IEEE Transactions on Industrial Informatics, 2022, 18(2): 869-879. |
21 | Ossorio-Castillo J, Pena-Brage F. Optimization of a refinery scheduling process with column generation and a quantum annealer[J/OL]. Optimization and Engineering, 2021, . |
22 | Lyu W X, Zhu Y, Huang D X, et al. A new strategy of integrated control and on-line optimization on high-purity distillation process[J]. Chinese Journal of Chemical Engineering, 2010, 18(1): 66-79. |
23 | Gao X Y, Shang C, Jiang Y H, et al. Refinery scheduling with varying crude: a deep belief network classification and multimodel approach[J]. AIChE Journal, 2014, 60(7): 2525-2532. |
24 | Gao X Y, Jiang Y H, Chen T, et al. Optimizing scheduling of refinery operations based on piecewise linear models[J]. Computers & Chemical Engineering, 2015, 75: 105-119. |
25 | Shi L, Jiang Y H, Wang L, et al. Refinery production scheduling involving operational transitions of mode switching under predictive control system[J]. Industrial & Engineering Chemistry Research, 2014, 53(19): 8155-8170. |
26 | 张璐. 炼油厂全流程生产调度的模型重构和两层算法研究[D]. 北京: 清华大学, 2016. |
Zhang L. Research on the reformulation and two-level algorithm for overall refinery production scheduling[D]. Beijing: Tsinghua University, 2016. | |
27 | 韩彪, 江永亨, 王凌, 等. 基于即时交货的离散时间模型及其在炼油过程调度优化中的应用[J]. 控制与决策, 2020, 35(6): 1361-1368. |
Han B, Jiang Y H, Wang L, et al. Instant delivery based discrete-time model and its application in refinery process scheduling optimization[J]. Control and Decision, 2020, 35(6): 1361-1368. | |
28 | General Algebraic Modeling System[CP/OL]. . |
29 | 魏传江, 王浩, 谢新民, 等. GAMS用户指南[M]. 北京: 中国水利水电出版社, 2009. |
Wei C J, Wang H, Xie X M, et al. GAMS User Guide[M]. Beijing: China Water & Power Press, 2009. | |
30 | Ferris M C, Jain R, Dirkse S. GDXMRW: interfacing GAMS and MATLAB[R/OL]. . |
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