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Cyber attacks on PMU placement in a smart grid: Characterization and optimization

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  • Ding, Weiyong
  • Xu, Maochao
  • Huang, Yu
  • Zhao, Peng
  • Song, Fengyi

Abstract

Phasor measurement units (PMUs) have been integrated into the smart grid for monitoring the operational state of system and improving the reliability. Due to the high cost of PMU installment, the optimal placement strategies have attracted considerable attention in the literature. However, the impacts of cyber threats on the placement have been largely ignored owing to the cyber complexities. This paper initializes the study on the optimal PMU placement in a smart grid under the cyber threats. A probabilistic model is developed for assessing the unobservable risk of the power grid. We characterize the impacts of several cyber factors on the PMU placements including the number of directly attacked PMUs, the dependence among attack outcomes, and risk propagation. We further study the impacts of cyber attacks on the allocation strategies under a bi-level placement model. In particular, a novel ‘greedy’ algorithm for PMU placement is introduced with the presence of cyber risks. Our studies show that the cyber risk can significantly increase the unobservability risk of a power system which in turn requires additional PMU allocations, and the dependence among cyber attacks can lead to more unobservable risk.

Suggested Citation

  • Ding, Weiyong & Xu, Maochao & Huang, Yu & Zhao, Peng & Song, Fengyi, 2021. "Cyber attacks on PMU placement in a smart grid: Characterization and optimization," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:reensy:v:212:y:2021:i:c:s0951832021001344
    DOI: 10.1016/j.ress.2021.107586
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    References listed on IDEAS

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    Cited by:

    1. Diao, Xiaoxu & Zhao, Yunfei & Smidts, Carol & Vaddi, Pavan Kumar & Li, Ruixuan & Lei, Hangtian & Chakhchoukh, Yacine & Johnson, Brian & Blanc, Katya Le, 2024. "Dynamic probabilistic risk assessment for electric grid cybersecurity," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Ding, Zhetong & Chen, Chunyu & Cui, Mingjian & Bi, Wenjun & Chen, Yang & Li, Fangxing, 2021. "Dynamic game-based defensive primary frequency control system considering intelligent attackers," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Badrsimaei, Hamed & Hooshmand, Rahmat-Allah & Nobakhtian, Soghra, 2023. "Observable placement of phasor measurement units for defense against data integrity attacks in real time power markets," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Wu, Shimeng & Jiang, Yuchen & Luo, Hao & Zhang, Jiusi & Yin, Shen & Kaynak, Okyay, 2022. "An integrated data-driven scheme for the defense of typical cyber–physical attacks," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    5. Aslani, Mehrdad & Faraji, Jamal & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2022. "A novel clustering-based method for reliability assessment of cyber-physical microgrids considering cyber interdependencies and information transmission errors," Applied Energy, Elsevier, vol. 315(C).
    6. Berghout, Tarek & Benbouzid, Mohamed, 2022. "EL-NAHL: Exploring labels autoencoding in augmented hidden layers of feedforward neural networks for cybersecurity in smart grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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