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Forecasting the State of Components of Smart Grids for Early Detection of Cyberattacks

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Abstract

The author proposes an approach for predicting the state of Smart Grid components, which is based on a combination of the mathematical techniques of the Kalman filter and machine learning. Prediction of the state will make it possible to detect cyberattacks implemented against a Smart Grid at an early stage.

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REFERENCES

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Funding

This study was carried out as part of a scholarship of the President of the Russian Federation to young scientists and graduate students SP-1932.2019.5.

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Authors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic University, 195251, St. Petersburg, Russia

    D. S. Lavrova

Authors
  1. D. S. Lavrova
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Corresponding author

Correspondence to D. S. Lavrova.

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The authors declare that they have no conflict of interest.

Additional information

Translated by K. Lazarev

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Cite this article

Lavrova, D.S. Forecasting the State of Components of Smart Grids for Early Detection of Cyberattacks. Aut. Control Comp. Sci. 53, 1023–1025 (2019). https://doi.org/10.3103/S0146411619080133

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  • DOI: https://doi.org/10.3103/S0146411619080133

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