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Quantitative modelling and analysis of a Chinese smart grid: a stochastic model checking case study

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Abstract

Cyber-physical systems integrate information and communication technology with the physical elements of a system, mainly for monitoring and controlling purposes. The conversion of traditional power grid into a smart grid, a fundamental example of a cyber-physical system, raises a number of issues that require novel methods and applications. One of the important issues in this context is the verification of certain quantitative properties of the system. In this paper, we consider a specific Chinese smart grid implementation as a case study and address the verification problem for performance and energy consumption. We employ stochastic model checking approach and present our modelling and analysis study using PRISM model checker.

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Notes

  1. This implementation is undertaken by Wuxi SensingNet Industrialization Research Institute.

  2. These values are different from the ones used in [8] and [9], because of the hardware changes in the real smart grid implementation.

  3. The energy cost of transmitting 1 kB on a distance of 100 m is approximately the same as the energy required by a general-purpose processor of 100 MIPS/W to execute 3 million instructions [10].

  4. Exponential distribution is the only memoryless continuous distribution. Its discrete-time equivalent is the geometric distribution.

  5. If none of the neighbouring towers are available, then BN will transmit its data to a second-order neighbour.

References

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  7. Kwiatkowska, M., Norman, G., Parker, D.: PRISM 4.0: Verification of probabilistic real-time systems. In: Gopalakrishnan, G., Qadeer, S. (eds.) Proc. 23rd International Conference on Computer Aided Verification (CAV’11), LNCS, vol. 6806, pp. 585–591. Springer, Berlin (2011)

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  9. Yüksel, E., Nielson, H.R., Nielson, F., Zhu, H., Huang, H.: Modelling chinese smart grid: a Stochastic Model Checking Case Study. Tech. Rep. IMM-Technical Report-2012-02, DTU Informatics (2012)

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  16. Mccanne, S., Floyd, S., Fall, K.: The network simulator. http://nsnam.isi.edu/nsnam

  17. OPNET Technologies Inc: OPNET simulator. http://www.opnet.com

  18. The PRISM model checker website. http://www.prismmodelchecker.org/

  19. The formal models for the modelling and analysis of the chinese smart grid. http://www2.imm.dtu.dk/people/ender/csg/

  20. Yüksel, E.: Qualitative and quantitative security analyses for zigbee wireless sensor networks. Ph.D. thesis, Technical University of Denmark, Department of Informatics and Mathematical Modeling, Language-Based Technology, Kgs. Lyngby, Denmark (2011)

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Authors and Affiliations

  1. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark

    Ender Yüksel, Hanne Riis Nielson & Flemming Nielson

  2. Shanghai Key Laboratory of Trustworthy Computing, Softwarep Engineering Institute, East China Normal University, Shanghai, China

    Huibiao Zhu

  3. Wuxi SensingNet Industrialization Research Institute, Wuxi, China

    Heqing Huang

Authors
  1. Ender Yüksel
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  2. Hanne Riis Nielson
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  3. Flemming Nielson
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  4. Huibiao Zhu
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  5. Heqing Huang
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Corresponding author

Correspondence to Ender Yüksel.

Additional information

This work was supported in part by the IDEA4CPS project granted by the Danish Research Foundation for Basic Research (No. DNRF86-10) and National Natural Science Foundation of China, and in part by MT-LAB, a VKR Centre of Excellence for the Modelling of Information Technology. Huibiao Zhu was supported by National High Technology Research and Development Program of China (No. 2012AA011205), National Natural Science Foundation of China (No. 61361136002 and No. 61321064), Shanghai Knowledge Service Platform Project (No. ZF1213) and Shanghai Minhang Talent Project.

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Yüksel, E., Nielson, H.R., Nielson, F. et al. Quantitative modelling and analysis of a Chinese smart grid: a stochastic model checking case study. Int J Softw Tools Technol Transfer 16, 421–435 (2014). https://doi.org/10.1007/s10009-014-0311-8

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  • DOI: https://doi.org/10.1007/s10009-014-0311-8

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