Research and construction of digital twin intelligent ethylene plant

doi:10.11949/0438-1157.20221473

Abstract

Abstract:

Digital twin is considered to be an effective means to realize the interaction and integration of the information world and the physical world by practicing advanced concepts such as intelligent manufacturing and the industrial internet. It has attracted the attention of academic and business circles, especially the landing application of digital twin. Based on the research and construction work of Sinopec digital twin intelligent ethylene plant, this paper first described the definition and overall architecture of Sinopec digital twin intelligent plant. Secondly, based on the complete set of million-ton-level ethylene technology for complex raw materials, the research proposes a digital twin intelligent ethylene plant construction idea and corresponding key technologies that integrate and innovate “software of complete set of technical achievements, digitalization of engineering construction delivery, and intelligent operation of petrochemical plants”. The digital twin intelligent ethylene plant provided valuable experience for the construction of Sinopec’s intelligent plant 3.0, and lays a foundation for further extending ICT technology to the core devices of the aromatic hydrocarbon industry chain, coal chemical industry chain, and oil refining industry chain, and promoting high-quality development of petrochemical industry.

Key words: digital twin, ethylene, intelligent plant, industrial internet, process system engineering

摘要：

数字孪生被认为是实践智能制造与工业互联网等战略、实现信息世界与物理世界交互集成的有效技术手段，备受学术界和企业界的关注，尤其数字孪生的落地应用更是关注热点。基于中国石化数字孪生智能乙烯工厂的开发及工业应用工作，首先阐述了石化数字孪生智能工厂的定义及总体架构。其次，基于复杂原料百万吨级乙烯成套技术，研究提出了“成套技术成果软件化、工程建设交付数字化、石化工厂运营智能化”融合创新的数字孪生智能乙烯工厂构建思路以及相应的关键技术。数字孪生智能乙烯工厂为中国石化智能工厂3.0建设提供了宝贵经验，为进一步推广到芳烃产业链、煤化工产业链、炼油产业链的核心装置，推动石化工业的高质量发展奠定了基础。

关键词: 数字孪生, 乙烯, 智能工厂, 工业互联网, 过程系统工程

CLC Number:

TE 6

Zizong WANG, Hansheng SUO, Xueliang ZHAO. Research and construction of digital twin intelligent ethylene plant[J]. CIESC Journal, 2023, 74(3): 1175-1186.

王子宗, 索寒生, 赵学良. 数字孪生智能乙烯工厂研究与构建[J]. 化工学报, 2023, 74(3): 1175-1186.

Figures/Tables 6

Fig.1 Construction of petrochemical digital twin intelligent plant

Fig.2 Architecture of petrochemical digital twin intelligent plant

Fig.3 Digital twin industrial data

Fig.4 Digital twin industrial model

Fig.5 Digital twin industrial application

Fig.6 Cloud edge computing synergistic framework

References 31

1	Grieves M W. Product lifecycle management: the new paradigm for enterprises[J]. International Journal of Product Development, 2005, 2(1/2): 71-84.
2	Grieves M. Virtually Perfect: Driving Innovative and Lean Products Through Product Lifecycle Management[M]. Cocoa Beach: Space Coast Press, 2011.
3	Glaessgen E, Stargel D. The digital twin paradigm for future NASA and US air force vehicles[C]//53th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference.Honolulu, Hawaii. Reston, Virginia: AIAA, 2012: 1818.
4	Gockel B, Tudor A, Brandyberry M, et al. Challenges with structural life forecasting using realistic mission profiles[C]//53th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Honolulu, Hawaii. Reston, Virginia: AIAA, 2012: 1813.
5	He Y, Guo J C, Zheng X L. From surveillance to digital twin: challenges and recent advances of signal processing for industrial internet of things[J]. IEEE Signal Processing Magazine, 2018, 35(5): 120-129.
6	Prudencio E E, Bauman P T, Williams S V, et al. A dynamic data driven application system for real-time monitoring of stochastic damage[J]. Procedia Computer Science, 2013, 18: 2056-2065.
7	Industry Internet Consortium. Digital twins for industrial applications: definition, business values, design aspects, standards and use cases[EB/OL]. .
8	International Organization for Standardization. Automation systems and integration—Digital twin framework for manufacturing (part 1): Overview and general principles[EB/OL]. .
9	Madni A, Madni C, Lucero S. Leveraging digital twin technology in model-based systems engineering[J]. Systems, 2019, 7(1): 7.
10	陶飞, 刘蔚然, 刘检华, 等. 数字孪生及其应用探索[J]. 计算机集成制造系统, 2018, 24(1): 1-18.
	Tao F, Liu W R, Liu J H, et al. Digital twin and its potential application exploration[J]. Computer Integrated Manufacturing Systems, 2018, 24(1): 1-18.
11	陶飞, 张贺, 戚庆林, 等. 数字孪生十问: 分析与思考[J]. 计算机集成制造系统, 2020, 26(1): 1-17.
	Tao F, Zhang H, Qi Q L, et al. Ten questions towards digital twin: analysis and thinking[J]. Computer Integrated Manufacturing Systems, 2020, 26(1): 1-17.
12	Chu L Y, Park S H, Yamaguchi T, et al. Preparation of micron-sized monodispersed thermoresponsive core-shell microcapsules[J]. Langmuir, 2002, 18(5): 1856-1864.
13	龚俊波, 陈明洋, 黄翠, 等. 面向清洁生产的制药结晶[J]. 化工学报, 2015, 66(9): 3271-3278.
	Gong J B, Chen M Y, Huang C, et al. Clean production of pharmaceutical crystallization[J]. CIESC Journal, 2015, 66(9): 3271-3278.
14	李培根, 陈立平. 在孪生空间重构工程教育: 意识与行动[J]. 高等工程教育研究, 2021(3): 1-8.
	Li P G, Chen L P. Reconfigurating engineering education in twin spaces: consciousness and action[J]. Research in Higher Education of Engineering, 2021(3): 1-8.
15	Minerva R, Crespi N. Digital twins: properties, software frameworks, and application scenarios[J]. IT Professional, 2021, 23(1): 51-55.
16	Soni R, Tanmay D, Twinkle, et al. Digital twin: intersection of mind and machine[J]. International Journal of Computational Intelligence and IoT, 2019, 2(3): 667-670.
17	Rosen R, Wichert G V, Lo G, et al. About the importance of autonomy and digital twins for the future of manufacturing[J]. IFAC-PapersOnLine, 2015, 48(3): 567-572.
18	Alam K M, El Saddik A. C2PS: a digital twin architecture reference model for the cloud-based cyber-physical systems[J]. IEEE Access, 2017, 5: 2050-2062.
19	Schluse M, Rossmann J. From simulation to experimentable digital twins: simulation-based development and operation of complex technical systems[C]//2016 IEEE International Symposium on Systems Engineering. Edinburgh, UK: IEEE, 2016: 1-6.
20	Bracht U. The digital factory between vision and reality[J]. Computers in Industry, 2005, 56(4): 325-333.
21	袁晴棠, 殷瑞钰, 曹湘洪, 等. 面向2035的流程制造业智能化目标、特征和路径战略研究[J]. 中国工程科学, 2020, 22(3): 148-156.
	Yuan Q T, Yin R Y, Cao X H, et al. Strategic research on the goals, characteristics, and paths of intelligentization of process manufacturing industry for 2035[J]. Strategic Study of CAE, 2020, 22(3): 148-156.
22	王基铭. 我国石化产业面临的挑战及对策建议[J]. 当代石油石化, 2015, 23(11): 1-7.
	Wang J M. Challenges facing China’s petrochemical industry and their countermeasure suggestions[J]. Petroleum ＆ Petrochemical Today, 2015, 23(11): 1-7.
23	王基铭. 生态文明建设与石油石化产业升级[J]. 化工学报, 2014, 65(2): 369-373.
	Wang J M. Construction of ecological civilization and upgradation of petrochemical industry[J]. CIESC Journal, 2014, 65(2): 369-373.
24	王子宗, 刘洪谦, 王基铭. 甲醇制丙烯分离流程的研究与优化[J]. 化工学报, 2019, 70(1): 136-145.
	Wang Z Z, Liu H Q, Wang J M. Research and optimization of separation technology of methanol to propylene[J]. CIESC Journal, 2019, 70(1): 136-145.
25	王子宗, 王基铭, 高立兵. 石化工业软件分类及自主工业软件成熟度分析[J]. 化工进展, 2021, 40(4): 1827-1836.
	Wang Z Z, Wang J M, Gao L B. Classification and maturity analysis on petrochemical industrial software[J]. Chemical Industry and Engineering Progress, 2021, 40(4): 1827-1836.
26	高立兵, 索寒生. 工业软件的发展推进石化工程设计数字化转型探析[J]. 石油化工设计, 2021, 38(2): 1-8.
	Gao L B, Suo H S. Development of industrial software promotes digital transformation of petrochemical engineering design[J]. Petrochemical Design, 2021, 38(2): 1-8.
27	李德芳, 索寒生. 加快智能工厂进程, 促进生态文明建设[J]. 化工学报, 2014, 65(2): 374-380.
	Li D F, Suo H S. Accelerate the process of smart plant, promote ecological civilization construction[J]. CIESC Journal, 2014, 65(2): 374-380.
28	Li D F, Suo H S, Liu W. System structure and network computing architecture of petrochemical cyber-physical system: overview and perspective[J]. The Canadian Journal of Chemical Engineering, 2019, 97(8): 2176-2188.
29	李德芳, 索寒生, 刘暄. 石化企业能源管理系统的研发与应用[J]. 化工学报, 2015, 66(1): 7-13.
	Li D F, Suo H S, Liu X. Development and application of energy management system for petrochemical enterprises[J]. CIESC Journal, 2015, 66(1): 7-13.
30	李德芳, 蒋白桦, 索寒生, 等. 石化企业能源优化系统设计与应用[J]. 化工学报, 2016, 67(1): 285-293.
	Li D F, Jiang B H, Suo H S, et al. Design and application of energy optimization system in petrochemical enterprise[J]. CIESC Journal, 2016, 67(1): 285-293.
31	李彦瑞, 杨春节, 张瀚文, 等. 流程工业数字孪生关键技术探讨[J]. 自动化学报, 2021, 47(3): 501-514.
	Li Y R, Yang C J, Zhang H W, et al. Discussion on key technologies of digital twin in process industry[J]. Acta Automatica Sinica, 2021, 47(3): 501-514.

[1]	Hao WANG, Zhenlei WANG. Model simplification strategy of cracking furnace coking based on adaptive spectroscopy method [J]. CIESC Journal, 2023, 74(9): 3855-3864.
[2]	Lingding MENG, Ruqing CHONG, Feixue SUN, Zihui MENG, Wenfang LIU. Immobilization of carbonic anhydrase on modified polyethylene membrane and silica [J]. CIESC Journal, 2023, 74(8): 3472-3484.
[3]	Chengying ZHU, Zhenlei WANG. Operation optimization of ethylene cracking furnace based on improved deep reinforcement learning algorithm [J]. CIESC Journal, 2023, 74(8): 3429-3437.
[4]	Mengmeng ZHANG, Dong YAN, Yongfeng SHEN, Wencui LI. Effect of electrolyte types on the storage behaviors of anions and cations for dual-ion batteries [J]. CIESC Journal, 2023, 74(7): 3116-3126.
[5]	Zhen LI, Bo ZHANG, Liwei WANG. Development and properties of PEG-EG solid-solid phase change materials [J]. CIESC Journal, 2023, 74(6): 2680-2688.
[6]	Qian LIU, Yu CAO, Qi ZHOU, Jingshan MU, Wei LI. Design of Ziegler-Natta catalyst modified with pore structure and preparation of UHMWPE with high impact resistance and low entanglement [J]. CIESC Journal, 2023, 74(3): 1092-1101.
[7]	Lei WANG, Yong JIANG, Dazhong ZHONG, Jiayuan LI, Genyan HAO, Qiang ZHAO, Jinping LI. Carbonized metal-organic framework for carbon dioxide reduction to ethylene and ethanol [J]. CIESC Journal, 2022, 73(8): 3576-3585.
[8]	Xiaoqiang FAN, Zhengliang HUANG, Jingyuan SUN, Jingdai WANG, Xiaofei WANG, Xiaobo HU, Guodong HAN, Yongrong YANG, Wenqing WU. Development of cloudy gas-liquid fluidized bed ethylene polymerization process and high performance products [J]. CIESC Journal, 2022, 73(6): 2742-2747.
[9]	Shiyi GE, Yao YANG, Zhengliang HUANG, Jingyuan SUN, Jingdai WANG, Yongrong YANG. Analyzing particle growth and morphology evolution of polyethylene based on electrostatic separation [J]. CIESC Journal, 2022, 73(4): 1585-1596.
[10]	Jianfei ZHANG, Jiajiang LIN, Xionglin LUO, Feng XU. Modeling analysis for product distribution control and optimization of heavy oil FCCU [J]. CIESC Journal, 2022, 73(3): 1232-1245.
[11]	Lixia WANG, Zhaojie BI, Miaolei SHI, Chen WANG, Dongfang WANG, Qian LI. Effect of blending mode and ratio of UHMWPE/PEG on the entanglement behavior and properties of UHMWPE [J]. CIESC Journal, 2022, 73(2): 933-940.
[12]	Bo ZHANG, Xiaofei CHEN, Siyao ZHAO, Xin ZHOU. Progress of ethane-selective adsorbents for efficient purification of ethylene [J]. CIESC Journal, 2022, 73(10): 4255-4267.
[13]	GAO Shuaitao, LIU Xueke, ZHANG Li, LIU Fen, YU Jiang, SHANG Jianfeng, OU Tianxiong, ZHOU Zheng, CHEN Pingwen. Aspen Plus simulation on selective separation of high concentration acid gas of H₂S and CO₂ [J]. CIESC Journal, 2021, 72(S1): 413-420.
[14]	Xingchu HE,Dezhen CHEN,Zhenfei MEI,Batuer ADILI,Qing AN. ReaxFF MD study on the pyrolysis of PE catalyzed by CaO and the effect of H₂O on the catalytic process and mechanism analysis [J]. CIESC Journal, 2021, 72(9): 4665-4674.
[15]	LIANG Xingtang, LI Fengzhi, ZHONG Shuming, ZHANG Ruirui, JIAO Shufei, WANG Shuangshuang, YIN Yanzhen. In-situ modification of porous juncus with polyethyleneimine for efficient capture of Cr(Ⅵ) from wastewater [J]. CIESC Journal, 2021, 72(6): 3380-3389.