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Transactive Energy to Thwart Load Altering Attacks on Power Distribution Systems

Author

Listed:
  • Samuel Yankson

    (EECE Department, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

  • Mahdi Ghamkhari

    (EECE Department, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

Abstract

The automatic generation control mechanism in power generators comes into operation whenever an over-supply or under-supply of energy occurs in the power grid. It has been shown that the automatic generation control mechanism is highly vulnerable to load altering attacks. In this type of attack, the power consumption of multiple electric loads in power distribution systems is remotely altered by cyber attackers in such a way that the automatic generation control mechanism is disrupted and is hindered from performing its pivotal role. The existing literature on load altering attacks has studied implementation, detection, and location identification of these attacks. However, no prior work has ever studied design of an attack-thwarting system that can counter load altering attacks, once they are detected in the power grid. This paper addresses the above shortcoming by proposing an attack-thwarting system for countering load altering attacks. The proposed system is based on provoking real-time adjustment in power consumption of the flexible loads in response to the frequency disturbances caused by the load altering attacks. To make the adjustments in-proportion to the frequency disturbances, the proposed attack-thwarting system uses a transactive energy framework to establish a coordination between the flexible loads and the power grid operator.

Suggested Citation

  • Samuel Yankson & Mahdi Ghamkhari, 2019. "Transactive Energy to Thwart Load Altering Attacks on Power Distribution Systems," Future Internet, MDPI, vol. 12(1), pages 1-14, December.
  • Handle: RePEc:gam:jftint:v:12:y:2019:i:1:p:4-:d:301440
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    References listed on IDEAS

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    1. Peter Cramton, 2017. "Electricity market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 589-612.
    2. Hong, Tao & Fan, Shu, 2016. "Probabilistic electric load forecasting: A tutorial review," International Journal of Forecasting, Elsevier, vol. 32(3), pages 914-938.
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    Cited by:

    1. Om P. Malik, 2020. "Global Trends and Advances Towards a Smarter Grid and Smart Cities," Future Internet, MDPI, vol. 12(2), pages 1-3, February.
    2. Juan Ospina & David M. Fobes & Russell Bent, 2023. "On the Feasibility of Market Manipulation and Energy Storage Arbitrage via Load-Altering Attacks," Energies, MDPI, vol. 16(4), pages 1-16, February.

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