Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter August 5, 2022

Automatic monitoring system of power equipment based on Internet of Things technology

  • Xianglong Jiang ORCID logo EMAIL logo

Abstract

With the rapid development of the social economy, the power industry is also developing rapidly, the electricity load is increasing, and the power grid structure is becoming increasingly complex, people put forward higher requirements for improving the reliability of power supply, the emergence of Internet of Things technology can meet people’s urgent needs in a timely manner. How to use the advanced Internet of Things technology to realize the automation of power equipment is an inevitable trend in the development of power systems, and it is also the technical driving force for the development of power equipment. Due to the problems of information islanding, simplification, and security in traditional power equipment monitoring systems, this paper studies the automation of power equipment monitoring systems based on the Internet of Things. The experimental results show that the introduction of the Internet of Things technology into the automatic monitoring system of power equipment increases the utilization rate of power equipment by 4.33%. In addition, the safety of power grid operation and the monitoring of power equipment are improved. Once the power equipment is abnormal, it will be detected in time to ensure the continuity of the power supply.


Corresponding author: Xianglong Jiang, College of Intelligent Manufacture, Chongqing Creation Vocational College, Yongchuan 402160, Chongqing, China, E-mail:

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

1. Lin, YH, Tsai, MS. An advanced home energy management system facilitated by nonintrusive load monitoring with automated multiobjective power scheduling. IEEE Trans Smart Grid 2017;6:1839–51.10.1109/TSG.2015.2388492Search in Google Scholar

2. Kuzmenko, AP, Saburov, SV, Korolenko, LA. Results of processing data from the automated seismometric monitoring system of the Zeya HPP. Power Technol Eng 2021;55:487–93. https://doi.org/10.1007/s10749-021-01386-0.Search in Google Scholar

3. Chen, H, Liang, H, Tang, M. The real-time automated monitoring system for lateral deflection of underground structures. Adv Civ Eng 2020;2020:1–11. https://doi.org/10.1155/2020/6102062.Search in Google Scholar

4. Amir, A, Cpkr, B, Rhr, C. Clinical experiences with a new system for automated hand hygiene monitoring: a prospective observational study. Am J Infect Control 2020;48:527–33.10.1016/j.ajic.2019.09.003Search in Google Scholar PubMed

5. Shmelova, T, Sikirda, Y, Sterenharz, A. Automated system for monitoring and diagnostics pilot’s emotional state in flight. Int J Inform Technol Syst Approach 2021;14:1–16. https://doi.org/10.4018/ijitsa.2021010101.Search in Google Scholar

6. Tritschler, N, Dugenske, A, Kurfess, T. An automated edge computing-based condition health monitoring system: with an application on rolling element bearings. J Manuf Sci Eng 2021;143:1–10. https://doi.org/10.1115/1.4049845.Search in Google Scholar

7. Kessili, A, Vollertsen, J, Nielsen, AH. Automated monitoring system for events detection in sewer network by distribution temperature sensing data measurement. Water Sci Technol J Int Assoc Water Pollut Res 2018;78:1499–508. https://doi.org/10.2166/wst.2018.425.Search in Google Scholar PubMed

8. Beyene, YD, Jantti, R, Tirkkonen, O. NB-IoT technology overview and experience from cloud-RAN implementation. IEEE Wireless Commun 2017;24:26–32. https://doi.org/10.1109/mwc.2017.1600418.Search in Google Scholar

9. Sisavath, C, Yu, L. Design and implementation of security system for smart home based on IOT technology. Procedia Comput Sci 2021;183:4–13. https://doi.org/10.1016/j.procs.2021.02.023.Search in Google Scholar

10. Zhang, X. Application of NB-IoT technology in urban lighting system. Int Core J Eng 2020;6:246–51.Search in Google Scholar

11. Wu, SJ, Chiang, RD, Chang, SH. An interactive telecare system enhanced with IoT technology. IEEE Pervasive Comput 2017;16:62–9. https://doi.org/10.1109/mprv.2017.2940967.Search in Google Scholar

12. Almomani, DA, Al-Nawasrah, A, Alomoush, W, Al-Abweh, M, Alrosan, A, Gupta, BB. Information management and IoT technology for safety and security of smart home and farm systems. J Global Inf Manag 2021;29:1–25. https://doi.org/10.4018/jgim.20211101.oa21.Search in Google Scholar

13. Quionez, Y, Lizarraga, C, Aguayo, R. Communication architecture based on IoT technology to control and monitor pets feeding. J Univers Comput Sci 2021;27:190–207.10.3897/jucs.65094Search in Google Scholar

14. Cheng, Y, Zhao, X, Wu, J. Research on the smart medical system based on NB-IoT technology. Mobile Inf Syst 2021;2021:1–10. https://doi.org/10.1155/2021/7801365.Search in Google Scholar

15. Svalestuen, F, Knotten, V, Lædre, O, Drevland, F, Lohne, J. Using building information model (BIM) devices to improve information flow and collaboration on construction sites. Electron J Inf Technol Construct 2017;22:204–19.Search in Google Scholar

16. Sang, Y, Tingyu, S, Kang, P. Study on load monitoring and demand side management strategy of chemical enterprise. Automat Control Comput Sci 2021;55:534–45. https://doi.org/10.3103/s0146411621060080.Search in Google Scholar

17. Huo, Y, Dong, X, Xu, W. 5G cellular user equipment: from theory to practical hardware design. IEEE Access 2017;5:13992–4010. https://doi.org/10.1109/access.2017.2727550.Search in Google Scholar

18. Noury, A, Vergara-Cruz, J, Morfin, P. Layering transitions in superfluid helium adsorbed on a carbon nanotube mechanical resonator. Phys Rev Lett 2019;122:165301–6. https://doi.org/10.1103/physrevlett.122.165301.Search in Google Scholar

19. Ko, JH, Mudassar, BA, Mukhopadhyay, S. An energy-efficient wireless video sensor node for moving object surveillance. IEEE Trans Multi-Scale Comput Syst 2017;1:7–18.10.1109/TMSCS.2015.2478469Search in Google Scholar

20. Abdulmohsin, HA, Wahab, H, Hossen, A. A new hybrid feature selection method using T-test and fitness function. Comput Mater Contin 2021;68:3997–4016.10.32604/cmc.2021.014840Search in Google Scholar

21. Zheng, F, Zecchin, AC, Newman, JP. An adaptive convergence-trajectory controlled ant colony optimization algorithm with application to water distribution system design problems. IEEE Trans Evol Comput 2017;21:773–91. https://doi.org/10.1109/tevc.2017.2682899.Search in Google Scholar

Received: 2022-05-09
Accepted: 2022-07-15
Published Online: 2022-08-05

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 26.4.2024 from https://www.degruyter.com/document/doi/10.1515/ijeeps-2022-0144/html
Scroll to top button