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Network Recovery for Large-Scale Failures in Smart Grid by Simulation

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Abstract

Large-scale natural disaster or malicious attacks could cause serious damage to the power communication network in smart grid. If the damaged network cannot be repaired timely, great threat will be brought to the secure and stable operation of power grid. Therefore, an importance-based recovery method for large-scale failure has been proposed in smart grid by simulation. Firstly, the link importance for the whole network is calculated according to the solution of the link importance for the services type and the importance of services type for the power communication network. Secondly, a fault recovery model with the sum of the importance of each fault link has been established to recover more important communication services under the condition of limited resources. Finally, we propose a heuristic algorithm to reduce the expenditure of time, and then compare the results of the model with the 0–1 integer programming method to verify the feasibility of the method. The experimental results show that the links which carry high-priority can get priority to be repaired in the paper, thus it ensures the safe and stable operation of power communication network.

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Acknowledgement

This work was supported by the Natural Science Foundation of China grant No. 61472037; the Fundamental Research Funds for the Central Universities 2017 MS113.

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Correspondence to Huibin Jia .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Jia, H., Zheng, H., Gai, Y., Xu, D. (2019). Network Recovery for Large-Scale Failures in Smart Grid by Simulation. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_46

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  • DOI: https://doi.org/10.1007/978-3-030-32216-8_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32215-1

  • Online ISBN: 978-3-030-32216-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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