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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
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
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)
Mahafza, B.R., Elsherbeni, A.Z.: MATLAB Simulations for Radar Systems Design. A CRC Press Company (2004)
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
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
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)
Gray, J.: Jim gray on escience: a transformed scientific method. In: The Fourth Paradigm: Data-Intensive Scientific Discovery, pp. xvii–xxxi (2009)
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)
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)
Yuan, Y., Ardakanian, O., Low, S., et al.: On the inverse power flow problem. arXiv preprint arXiv:1610.06631 (2016)
Chen, Y.C., Wang, J., DomÃnguez-GarcÃa, A.D., et al.: Measurement-based estimation of the power flow Jacobian matrix. IEEE Trans. Smart Grid 7(5), 2507–2515 (2015)
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)
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)
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
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Singapore Pte Ltd.
About this paper
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)