Skip to main content

Application of Digital Twin in the Security Protection of the Internet of Things in Power System

  • Conference paper
  • First Online:
Big Data and Security (ICBDS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1563))

Included in the following conference series:

  • 1024 Accesses

Abstract

This paper provides an overview of DT and PSDT, and explores the potential applications of PSDT. For power digital twin, its purpose is to promote the effective use of data flow, with virtual deduction means, combined with real-time situation perception, to get a full understanding of the power system, and then can play an auxiliary role in the formulation of regulatory decisions. Different from the current simulation software, PSDT has the features of data-driven, real-time interaction and closed-loop feedback. This paper analyzes the background and purpose of PSDT from the perspective of engineering and scientific science, and expounds the ideas and characteristics of construction, and further designs the implementation framework of PSDT. Finally, the application status and prospects of PSDT in many fields of power systems are clarified. The research results of this paper promote the development of dt technology and the application of data science in engineering.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Jia, Y., Peng, Z.: The analysis and simulation of communication network in Iridium system based on OPNET. In: The 2nd IEEE International Conference on Information Management and Engineering, Chengdu, China, 16–18 April 2010

    Google Scholar 

  2. Connors, D.P., Ryu, B., Dao, S.: Modeling and simulation of broadband satellite networks Part I: medium access control for QoS provisioning. IEEE Commun. Mag. 37(3), 72–79 (1999)

    Google Scholar 

  3. Mahafza, B.R., Elsherbeni, A.Z.: MATLAB Simulations for Radar Systems Design. A CRC Press Company (2004)

    Google Scholar 

  4. Yu, J., Zong, P.: The analysis and simulation of communication network in iridium system based on OPNET. In: The 2nd IEEE International Conference on Information Management and Engineering, Chengdu, China, 16–18 April 2010

    Google Scholar 

  5. Wang, X., Zong, P., Yu, J.: Link analyzing and simulation of TDRSS based on OPNET. In: The International Conference on Communications and Mobile Computing, Shenzhen, China, 12–14 April 2010

    Google Scholar 

  6. He, X., Ai, Q., Qiu, R.C., et al.: A big data architecture design for smart grids based on random matrix theory. IEEE Trans. Smart Grid 8(2), 674–686 (2015)

    Google Scholar 

  7. Gray, J.: Jim gray on escience: a transformed scientific method. In: The Fourth Paradigm: Data-Intensive Scientific Discovery, pp. xvii–xxxi (2009)

    Google Scholar 

  8. Hong, T., Chen, C., Huang, J., et al.: Guest editorial big data analytics for grid modernization. IEEE Trans. Smart Grid 7(5), 2395–2396 (2016)

    Article  Google Scholar 

  9. Burges, C., Shaked, T., Renshaw, E., et al.: Learning to rank using gradient descent. In: Proceedings of the 22nd International Conference on Machine learning (ICML-05), pp. 89–96 (2005)

    Google Scholar 

  10. Yuan, Y., Ardakanian, O., Low, S., et al.: On the inverse power flow problem. arXiv preprint arXiv:1610.06631 (2016)

  11. Chen, Y.C., Wang, J., Domínguez-García, A.D., et al.: Measurement-based estimation of the power flow Jacobian matrix. IEEE Trans. Smart Grid 7(5), 2507–2515 (2015)

    Article  Google Scholar 

  12. Kelly, J., Knottenbelt, W.: Neural nilm:deep neural networks applied to energy disaggregation. In: Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments, pp. 55–64. ACM (2015)

    Google Scholar 

  13. Xu, S., Qiu, C., Zhang, D., et al.: A deep learning approach for fault type identification of transmission line. In: Proceedings of the CSEE, vol. 39, no. 1, pp. 65–74 (2019)

    Google Scholar 

  14. Boschert, S., Rosen, R.: Digital twin—the simulation aspect. In: Hehenberger, P., Bradley, D. (eds.) Mechatronic Futures, pp. 59–74. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-32156-1_5

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chen, Y., Zhang, Z., Tang, N. (2022). Application of Digital Twin in the Security Protection of the Internet of Things in Power System. In: Tian, Y., Ma, T., Khan, M.K., Sheng, V.S., Pan, Z. (eds) Big Data and Security. ICBDS 2021. Communications in Computer and Information Science, vol 1563. Springer, Singapore. https://doi.org/10.1007/978-981-19-0852-1_17

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-0852-1_17

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-0851-4

  • Online ISBN: 978-981-19-0852-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics