Research on industrial Internet of Things and power grid technology application based on knowledge graph and data asset relationship model

被引:1
作者
Wang, Xue [1 ]
Ma, Le [1 ]
Yang, Zhenwei [1 ]
机构
[1] Internet Div State Grid Gansu Elect Power Co, Lanzhou, Peoples R China
关键词
Knowledge graph; Data asset relationship; Industrial Internet of Things; Power grid technology;
D O I
10.2478/amns.2021.2.00285
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Power grid data asset management, maintaining the health and integrity of physical assets, optimising the allocation of physical assets, dynamically monitoring the distribution and operation of physical assets, and predicting the investment scale of operation and maintenance and technological transformation are important issues faced by power grid companies. First, the existing literature in this paper is sorted out to define the concept and characteristics of data assets. Then, a training model based on a knowledge graph and data asset relationship model is proposed. At the same time, the key technologies of the Industrial Internet of Things and the theoretical model framework of power grid technology are proposed, including device access, protocol conversion, edge data processing, connectivity, the first entry of data and the rapid growth of data volume. Finally, experiments are carried out to verify the framework proposed in this paper. Experiments show that the research on industrial Internet of Things and power grid technology based on knowledge graphs and data asset relationship model is of great significance for enterprises to exert data value and promote the development of the digital economy.
引用
收藏
页码:2605 / 2616
页数:11
相关论文
共 23 条
[1]  
Almarboui K, 2021, IOP C SERIES EARTH E
[2]  
Bao L S, 2018, ELECT POWER INFORM C
[3]  
Bo Chai, 2017 INT C APPL MATH
[4]  
Coppolino L, 2011, INT C COMPUTER SAFET
[5]  
Hu J, 2021, 2021 IEEE INT C POWE
[6]  
HUANG H, 2020, MATH PROBL ENG, V2020, P1, DOI DOI 10.1007/S42835-022-01032-3
[7]  
Kryukov A V, 2021, IOP C SERIES MAT SCI, V1151
[8]   Intelligent Agriculture Greenhouse Environment Monitoring System Based on IOT Technology [J].
Liu Dan ;
Cao Xin ;
Huang Chongwei ;
Ji Liangliang .
2015 INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION, BIG DATA AND SMART CITY (ICITBS), 2016, :487-490
[9]  
Luo M., 2020, Journal of Physics: Conference Series, V1601, DOI [10.1088/1742-6596/1601/3/032052, DOI 10.1088/1742-6596/1601/3/032052]
[10]   Resilient decentralized optimization of chance constrained electricity-gas systems over lossy communication networks [J].
Qian, Tong ;
Chen, Xingyu ;
Xin, Yanli ;
Tang, Wenhu ;
Wang, Lixiao .
ENERGY, 2022, 239