Digital Twin Technology for Smart Power Generation and Its Application Modes

doi:10.12096/j.2096-4528.pgt.20075

Abstract

Abstract:

As an important part of power system, the intelligent construction of power generation process is an important direction to promote the development of energy transformation in China. Combined with current situation and development trend of digital twin technology research, the concept and system of smart power generation were analyzed. Then the definition of digital twin in the field of smart power generation was proposed. Through function mapping, the digital twin architecture of smart power generation was constructed. A general method of deploying digital twin technology in smart power generation system was proposed. The application fields and modes of digital twin technology were summarized, and the main technology challenges in application were analyzed. The research results provide theoretical and methodological reference for the industrial development of digital twin technology in the field of power generation.

Key words: smart power generation, digital twin, application architecture, data driven

CLC Number:

TM61
TP391.9

Fang FANG,Xiaoning ZHANG,Dongyang LIANG,Qinghua WANG. Digital Twin Technology for Smart Power Generation and Its Application Modes[J]. Power Generation Technology, 2020, 41(5): 462-470.

References

1	国务院.国务院关于印发《中国制造2025》的通知[EB/OL].(2015-05-19)[2020-08-01].http://www.gov.cn/zhengce/content/2015-05/19/content_9784.htm.
1	The State Council.Notice of the State Council on issuing "Made in China 2025"[EB/OL].(2015-05-19)[2020-08-01].http://www.gov.cn/zhengce/content/2015-05/19/content_9784.htm.
2	国务院.国务院关于深化"互联网+先进制造业"发展工业互联网的指导意见[EB/OL].(2017-11-27)[2020-08-01].http://www.gov.cn/zhengce/content/2017-11/27/content_5242582.htm.
2	The State Council.Guiding opinions of the State Council on deepening "Internet + Advanced Manufacturing" and developing industrial internet[EB/OL].(2017-11-27)[2020-08-01].http://www.gov.cn/zhengce/content/2017-11/27/content_5242582.htm.
3	国务院.国务院关于印发新一代人工智能发展规划的通知[EB/OL].(2017-07-20)[2020-08-01].http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm.
3	The State Council.Notice of the State Council on issuing the development plan for the new generation of artificial intelligence[EB/OL].(2017-07-20)[2020-08-01].http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm.
4	刘吉臻, 王庆华, 房方, 等. 数据驱动下的智能发电系统应用架构及关键技术[J]. 中国电机工程学报, 2019, 39 (12): 3578- 3586.
4	Liu J Z , Wang Q H , Fang F , et al. Data-driven-based application architecture and technologies of smart power generation[J] Proceedings of the CSEE, 2019, 39 (12): 3578- 3586.
5	贾科华.独家专访\|刘吉臻:智能发电是第四次工业革命的大趋势[N].中国能源报, 2016-07-27.
5	Jia K H.Exclusive interview\|Liu Jizhen: Smart power generation is a major trend in the fourth industrial revolution[N].China Energy News, 2016-07-27.
6	耿海涛, 朱亚迪. 智能化联合循环电厂建设方案探讨[J]. 发电技术, 2018, 39 (6): 520- 525.
6	Geng H T , Zhu Y D . Construction scheme discussion for smart gas-fired power plant[J] Power Generation Technology, 2018, 39 (6): 520- 525.
7	吴智泉, 王政霞. 智慧风电体系架构研究[J]. 分布式能源, 2019, 4 (2): 8- 15.
7	Wu Z Q , Wang Z X . Smart wind power system architecture[J] Distributed Energy, 2019, 4 (2): 8- 15.
8	周怀春, 胡志方, 郭建军, 等. 面向智能发电的电站燃煤锅炉在线运行优化[J]. 分布式能源, 2019, 4 (3): 1- 7.
8	Zhou H C , Hu Z F , Guo J J , et al. On-line optimization of coal-fired boiler operation in power plants for smart power generation[J] Distributed Energy, 2019, 4 (3): 1- 7.
9	谌强, 朱亚迪. 燃机智能电厂框架下的厂级技术监督管理系统研究与开发[J]. 华电技术, 2020, 42 (2): 28- 32.
9	Shen Q , Zhu Y D . Research and development of plant-level technical supervision and management system under the framework of smart gas turbine power plant[J] Huadian Technology, 2020, 42 (2): 28- 32.
10	黄鹤, 秦岭, 喻洋洋, 等. 水光多能互补清洁能源智能发电技术[J]. 分布式能源, 2020, 5 (2): 21- 26.
10	Huang H , Qin L , Yu Y Y , et al. Smart-power generation technology of clean energy with water-light multi-energy complementary[J] Distributed Energy, 2020, 5 (2): 21- 26.
11	Grieves M . Product lifecycle management:driving the next generation of lean thinking[M]. New York: McGraw Hill Professional, 2005.
12	Glaessgen E, Stargel D.The digital twin paradigm for future NASA and U.S. Air Force vehicles[C]//53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference.2012: 1818.
13	Gartner Research.Top 10 strategic technology trends for 2019: digital twins[EB/OL].(2019-03-13)[2020-08-01].https://www.gartner.com/en/documents/3904569/top-10-strategic-technology-trends-for-2019-digital-twin.
14	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.
14	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.
15	陶飞, 程颖, 程江峰, 等. 数字孪生车间信息物理融合理论与技术[J]. 计算机集成制造系统, 2017, 23 (8): 1603- 1611.
15	Tao F , Cheng Y , Cheng J F , et al. Theories and technologies for cyber-physical fusion in digital twin shop-floor[J] Computer Integrated Manufacturing Systems, 2017, 23 (8): 1603- 1611.
16	Lu Y , Liu C , Kevin I , et al. Digital twin-driven smart manufacturing:connotation, reference model, applications and research issues[J] Robotics and computer-integrated manufacturing, 2020, 61, 101837- 101850.
17	Holler M, Uebernickel F, Brenner W.Digital twin concepts in manufacturing industries: a literature review and avenues for further research[C]//18th International Conference on Industrial Engineering (IJIE).2016: 1-9.
18	Qi Q , Tao F . Digital twin and big data towards smart manufacturing and Industry 4.0:360 degree comparison[J] IEEE Access, 2018, 6, 3585- 3593.
19	Kritzinger W , Karner M , Traar G , et al. Digital twin in manufacturing:a categorical literature review and classification[J] IFAC-Papers OnLine, 2018, 51 (11): 1016- 1022.
20	Venkatesan S , Manickavasagam K , Tengenkai N , et al. Health monitoring and prognosis of electric vehicle motor using intelligent-digital twin[J] IET Electric Power Applications, 2019, 13 (9): 1328- 1335.
21	Tao F , Cheng J , Qi Q , et al. Digital twin-driven product design, manufacturing and service with big data[J] The International Journal of Advanced Manufacturing Technology, 2018, 94, 3563- 3576.
22	Liu Y , Zhang L , Yang Y , et al. A novel cloud-based framework for the elderly healthcare services using digital twin[J] IEEE Access, 2019, 7, 49088- 49101.
23	Barricelli B R , Casiraghi E , Gliozzo J , et al. Human digital twin for fitness management[J] IEEE Access, 2020, 8, 26637- 26664.
24	Booyse W , Wilke D N , Heyns S . Deep digital twins for detection, diagnostics and prognostics[J] Mechanical Systems and Signal Processing, 2020, 140, 106612- 106636.
25	Bachelor G , Brusa E , Ferretto D , et al. Model-based design of complex aeronautical systems through digital twin and thread concepts[J] IEEE Systems Journal, 2020, 14 (2): 1568- 1579.
26	Goraj R.Digital twin of the rotor-shaft of a lightweight electric motor during aerobatics loads[J].Aircraft Engineering and Aerospace Technology, 2020, Early access, doi: 10.1108/AEAT-11-2019-0231.
27	Wanasinghe T R , Wroblewski L , Petersen B , et al. Digital twin for the oil and gas industry:overview, research trends, opportunities, and challenges[J] IEEE Access, 2020, 8, 104175- 104197.
28	Bevilacqua M , Bottani E , Ciarapica F E , et al. Digital twin reference model development to prevent operators' risk in process plants[J] Sustainability, 2020, 12 (3): 1088- 1103.
29	范海东. 基于数字孪生的智能电厂体系架构及系统部署研究[J]. 智能科学与技术学报, 2019, 1 (3): 241- 248.
29	Fan H D . Research on architecture and system deployment of intelligent power plant based on digital twin[J] Chinese Journal of Intelligent Science and Technology, 2019, 1 (3): 241- 248.
30	唐文虎,陈星宇,钱瞳,等.面向智慧能源系统的数字孪生技术及其应用[J/OL].中国工程科学, https://kns.cnki.net/kcms/detail/11.4421.G3.20200806.1706.012.html.
30	Tang W H, Chen X Y, Qian T, et al.Technologies and applications of digital twin for developing smart energy systems[J/OL].Strategic Study of CAE, https://kns.cnki.net/kcms/detail/11.4421.G3.20200806.1706.012.html.
31	Song X , Jiang T , Schlegel S , et al. Parameter tuning for dynamic digital twins in inverter-dominated distribution grid[J] IET Renewable Power Generation, 2019, 14 (5): 811- 821.
32	Zhou M , Yan J , Zhou X . Real-time online analysis of power grid[J] CSEE Journal of Power and Energy Systems, 2020, 6 (1): 236- 238.
33	Francisco A , Mohammadi N , Taylor J E . Smart city digital twin-enabled energy management:toward real-time urban building energy benchmarking[J] Journal of Management in Engineering, 2020, 36 (2): 4019045- 4019055.
34	沈沉, 贾孟硕, 陈颖, 等. 能源互联网数字孪生及其应用[J]. 全球能源互联网, 2020, 3 (1): 1- 13.
34	Shen C , Jia M S , Chen Y , et al. Digital twin of the energy internet and its application[J] Journal of Global Energy Interconnection, 2020, 3 (1): 1- 13.
35	于勇, 范胜廷, 彭关伟, 等. 数字孪生模型在产品构型管理中应用探讨[J]. 航空制造技术, 2017, (7): 41- 45.
35	Yu Y , Fan S T , Peng G W , et al. Study on application of digital twin model in product configuration management[J] Aeronautical Manufacturing Technology, 2017, (7): 41- 45.
36	Grieves M . Digital twin:manufacturing excellence through virtual factory replication[J] White Paper, 2014, 1, 1- 7.
37	Tao F , Zhang M . Digital twin shop-floor:a new shop-floor paradigm towards smart manufacturing[J] IEEE Access, 2017, 5, 20418- 20427.
38	Aaron P, Lane W.Industry 4.0 and the digital twin[EB/OL].(2017-05-12)[2020-08-01].https://www2.deloitte.com/us/en/insights/focus/industry-4-0/digital-twin-technology-smart-factory.html.
39	马虹哲. 智能电网信息安全威胁及防护关键技术研究[J]. 信息通信, 2017, (12): 162- 163.
39	Ma H Z . Research on smart grid information security threats and key technologies of protection[J] Information & Communications, 2017, (12): 162- 163.

[1]	Xiangyu WANG, Wuhui CHEN, Xiaolong GUO, Xiqiang CHANG. Review of Research on the Digitalization of Power Generation System [J]. Power Generation Technology, 2024, 45(1): 120-141.
[2]	Chao HUANG, Siqi BU, Qiyu CHEN, Hiu Hung LEE. Meta-Power: Next-Generation Smart Grid [J]. Power Generation Technology, 2022, 43(2): 287-304.
[3]	Bowen ZHOU, Chao XI, Guangdi LI, Bo YANG. Metaverse Application in Power Systems [J]. Power Generation Technology, 2022, 43(1): 1-9.