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Defended data transmission scheme based reliable metering for smart grid applications

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Abstract

To expand the usage, reliability, availability of power resources and some distribution system must be met which is conceivable by the support of present day information technologies. This paper concentrates on client support and electricity distribution, where payment of electric bills (counting energy utilization every month or year and association points of interest) should be possible with online arrangements. It is proposed a protected and reliable solution which joins the elements of the electrical system with the network systems to give better execution on informing issues, which is done given demand location. The electric readings of the client will be upgraded each month in the database which is kept up in the distributed storage. The client will be furnished with security keys to see the perusing values and perform payment of bills. To make the solution more available, the dynamic information will be kept up on different servers in various areas of the cloud, and there will be a service supplier who deals with the service request. The hardwired electric meter transmits the electrical reading, which turn accesses the particular service to make an entry for the specific association at the cloud. The usage data will be kept up at various area of the cloud, which is accessible with security, measures various clients. The customer availability is controlled with SCADA.

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References

  1. Kayastha, N., Niyato, D., Hossain, E., Han, Z.: Smart grid sensor data collection, communication, and networking: a tutorial. Wirel. Commun. Mobile Comput. 14(11), 1055–1087 (2012)

    Article  Google Scholar 

  2. NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 3.0, Smart Grid Interoperability Panel (SGIP), NIST Standard 1108R3, Oct 2013

  3. Fang, X., Misra, S., Xue, G., Yang, D.: Managing smart grid information in the cloud: opportunities, model, and applications. IEEE Netw. 26(4), 32–38 (2012)

    Article  Google Scholar 

  4. Bera, S., Misra, S., Rodrigues, J.: Cloud computing applications for smart grid: a survey. IEEE Trans. Parallel Distrib. Syst. (to be published)

  5. Tabassum, R., Nahrstedt, K., Rogers, E., Lui, K.-S.: SCAPACH: scalable password-changing protocol for smart grid device authentication. In: Proceedings of the 22nd International Conference on Computer and Communications networks, Nassau, pp. 1–5 (2013)

  6. The Transport Layer Security (TLS) Protocol Version 1.2, RFC Standard 5246, 2008

  7. Kim, Y.-J., Kolesnikov, V., Thottan, M.: Resilient end-to-end message protection for large-scale cyber-physical system communications. In: Proceedings of the IEEE 3rd International Conference on Conference on Smart Grid Communications (SmartGridComm), Tainan, Taiwan, 2012, pp. 193–198. DNP3 Secure Authentication Version 5, IEEE Standard 1815-2012 (2011)

  8. IEC Power Utility Automation, Technical Committee 57 (TC57), IEC Standard 61850 (2003)

  9. Vaidya, B., Makrakis, D., Mouftah, H.T.: Device authentication mechanism for smart energy home area networks. In: Proceedings of the IEEE ICCE, Las Vegas, USA, pp. 787–788 (2011)

  10. Kim, Y.-J., Kolesnikov, V., Kim, H., Thottan, M.: SSTP: a scalable and secure transport protocol for smart grid data collection. In: Proceedings of the IEEE International Conference on Smart Grid Communications. (SmartGridComm), Brussels, Belgium, pp. 161–166 (2011)

  11. Khalifa, T., Naik, K., Alsabaan, M., Nayak, A., Goel, N.: Transport protocol for smart grid infrastructure. In: Proceedings of the IEEE International Conference on Ubiquitous Future Networks, Jeju Island, Korea, pp. 320–332 (2010)

  12. Crossley, D.: The role of advanced metering and load control in supporting electricity networks. Tech. Rep. No 5 Task XV, International Energy Agency Demand Side Management Programme. Energy Futures Australia PTY LTD, Australia (2008)

  13. Mathieu, J.L., et al.: Examining uncertainty in demand response baseline models and variability in automated responses to dynamic pricing. In: 50th IEEE Conference on Decision and Control (CDC), pp. 4332–4339 (2011)

  14. Roozbehani, M., et al.: On the stability of wholesale electricity markets under real-time pricing. In: 49th IEEE Conference on Decision and Control (CDC), pp. 1911–1918 (2010)

  15. Ustun, T.S.: Fault current coefficient and time delay assignment for micro grid protection system with central protection unit. IEEE Trans. Power Syst. 28(2), 598–606 (2013)

    Article  Google Scholar 

  16. Lianordi, B.: An approach for real time voltage stability margin control via reactive power reserve sensitivities. IEEE Trans. Power Syst. 28(2), 615–625 (2013)

    Article  Google Scholar 

  17. Ziari, S.: Optimal distribution network reinforcement considering load growth, line loss, and reliability. IEEE Trans. Power Syst. 28(2), 587–597 (2013)

    Article  Google Scholar 

  18. Shao, S.: Development of physical-based demand response-enabled residential load models. IEEE Trans. Power Syst. 28(2), 607–614 (2013)

    Article  Google Scholar 

  19. Xie, T., et al.: SAREC: a security-aware scheduling strategy for real-time applications on clusters. In: Proceedings of the 34th International Conference on Parallel Processing, Oslo (2005)

  20. Islam, M.R., et al.: An architecture and a dynamic scheduling algorithm of grid for providing security for real-time data-intensive applications. Int. J. Netw. Manag. 21(5), 402–413 (2011)

    Article  Google Scholar 

  21. Shaaban, M.F.: DG allocation for benefit maximization in distribution networks. IEEE Trans. Power Syst. 28(2), 639–649 (2013)

    Article  Google Scholar 

  22. Stankovic, J.A., et al.: Deadline scheduling for real-time systems: EDF and related algorithms. Dordrecht, Kluwer (1998)

    Book  Google Scholar 

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Authors and Affiliations

  1. Periyar Maniammai University, Vallam, Thanjavur, 613 403, India

    K. Vedavalli

  2. Periyar Maniammai Institute of Science and Technology, Thanjavur, 613 403, India

    N. Muruganantham

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  1. K. Vedavalli
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  2. N. Muruganantham
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Correspondence to K. Vedavalli.

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Vedavalli, K., Muruganantham, N. Defended data transmission scheme based reliable metering for smart grid applications. Cluster Comput 22 (Suppl 6), 14277–14285 (2019). https://doi.org/10.1007/s10586-018-2286-9

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  • DOI: https://doi.org/10.1007/s10586-018-2286-9

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