Skip to main content
SpringerLink
Log in

The prediction of network efficiency in the smart grid

  • Published:
Electronic Commerce Research Aims and scope Submit manuscript

Abstract

AMI is the core infrastructure of a smart grid and it is expected to be used for many industrial fields. The components of AMI generally include a smart meter, DCU, and MDMS. In such a system, the smart meter measures power consumption and DCU collects information from smart meters and send their data to MDMS. The MDMS is an end server to get information of the power usage and store its log and data. Since there are a lot of devices such as smart meters and DCUs in AMI, it is important to maintain the suitable number of them. In particular, it is necessary to calculate the proper number of DCUs for efficient management of AMI. In this paper, we suggest a way to predict the proper number of DCUs and this proposed method is useful to predict the total performance of heterogeneous AMI. The simulation results show that AMI is greatly influenced by the difference of performance between DCUs in the heterogeneous AMI.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Aikebaier, A., Enokido, T., & Takizawa, M. (2011). Trustworthy group making algorithm in distributed systems. In HCIS 2011 (Vol. 1, p. 6).

    Google Scholar 

  2. Poh Ai Ling, A., & Masao, M. (2011). Selection of model in developing information security criteria for smart grid security system. Journal of Convergence, 2(1), 39–46.

    Google Scholar 

  3. Bennett, C., & Wicker, S. B. (2010). Decreased time delay and security enhancement recommendations for AMI smart meter networks. In Conference on innovative smart grid technologies (ISGT) (pp. 1–6).

    Chapter  Google Scholar 

  4. Li, F. (2007). Continuous locational marginal pricing (CLMP). IEEE Transactions on Power Systems, 22(4), 1638–1646.

    Article  Google Scholar 

  5. Li, F., & Bo, R. (2009). Congestion and price prediction under load variation. IEEE Transactions on Power Systems, 24(2), 911–922.

    Article  Google Scholar 

  6. Li, F., Qiao, W., Sun, H., Wan, H., Wang, J., Xia, Y., Xu, Z., & Zhang, P. (2010). Smart transmission grid: vision and framework. IEEE Transactions on Smart Grid, 1(2), 167–177.

    Article  Google Scholar 

  7. Bumiller, G., Lampe, L., & Hrasnica, H. (2010). Power line communications for large-scale control and automation systems. IEEE Communications Magazine, 48(4), 106–113.

    Article  Google Scholar 

  8. Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2011). Smart grid technologies: communication technologies and standards. IEEE Transactions on Smart Grid, 7(4), 529–539.

    Google Scholar 

  9. Luss, H., Neidhardt, A. L., & Krishan, K. R. (2009). An adaptive automated method for identity verification with performance guarantees. Electronic Commerce Research, 9(8), 225–242.

    Article  Google Scholar 

  10. Roozbehani, M., Dahleh, M., & Mitter, S. (2010). Dynamic pricing and stabilization of supply and demand in modern electric power grids. In Conference on smart grid communications (SmartGridComm) (pp. 543–548).

    Google Scholar 

  11. McDaniel, P., & Smith, S. W. (2009). Security and privacy challenges in the smart grid. IEEE Security & Privacy, 7(3), 75–77.

    Article  Google Scholar 

  12. Hsu, P.-H., Tang, W., Tsai, C., & Cheng, B.-C. (2011). Two-layer security scheme for AMI system. Journal of Convergence, 2(1), 47–52.

    Google Scholar 

  13. Paudyal, S., Canizares, C., & Bhattacharya, K. (2011). Optimal operation of distribution feeders in smart grids. IEEE Transactions on Smart Grid, 58(11), 4495–4503.

    Google Scholar 

  14. Silas, S., Ezra, K., & Blessing Rajsingh, E. (2012). A novel fault tolerant service selection framework for pervasive computing. In HCIS 2012 (Vol. 2, p. 5).

    Google Scholar 

  15. Misra, S. K., & Wickamasinghe, N. (2004). Security of a mobile transaction: a trust model. Electronic Commerce Research, 4(4), 359–372.

    Article  Google Scholar 

  16. Loureiro, S., Molva, R., & Pannetrat, A. (2001). Secure data collection with updates. Electronic Commerce Research, 1(1), 119–130.

    Article  Google Scholar 

  17. Yeo, S., & Lee, H.-H. S. (2011). Using mathematical modeling in provisioning a heterogeneous cloud computing environment. Computer, 44(8), 52–62.

    Google Scholar 

  18. Röhrig, S., & Knorr, K. (2004). Security analysis of electronic business processes. Electronic Commerce Research, 4(1), 59–81.

    Article  Google Scholar 

  19. Gungor, V. C., Lu, B., & Hancke, G. P. (2010). Opportunities and challenges of wireless sensor networks in smart grid. IEEE Transactions on Smart Grid, 57(10), 3557–3564.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea

    Sung-Min Jung

  2. Dept. of Liberal Art, Seoul Theological University, Seoul, Korea

    Tae-Kyung Kim

  3. Dept. of Computer Engineering, Korea University of Technology and Education, Cheonan, Korea

    Hee-Suk Seo

  4. Dept. of Architecture Engineering, Korea University of Technology and Education, Cheonan, Korea

    Seung-Jae Lee

  5. Dept. of Information Security Engineering, Soonchunhyang University, Asan, Korea

    Jin Kwak

Authors
  1. Sung-Min Jung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tae-Kyung Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hee-Suk Seo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Seung-Jae Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jin Kwak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jin Kwak.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jung, SM., Kim, TK., Seo, HS. et al. The prediction of network efficiency in the smart grid. Electron Commer Res 13, 347–356 (2013). https://doi.org/10.1007/s10660-013-9124-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10660-013-9124-1

Keywords

Search

Navigation