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Original Article

Anomaly Detection in Smart Grids: A PMU-Driven Approach

  • Paper ID 287
  • Volume 6, Issue 2
  • Pages 98-103
  • Published Online: March-April 2026
  • 65 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Mareedu Premsagar1
  • Malladi Pavan Vikas2
  • Dr. Vijay Ramalingam3

1 2 3 Department of Computer Science Engineering, Sathyabhma Institute of Science and Technology Chennai, Tamilnadu, India.

Article Information

Published Online
March-April 2026
Pages
98-103
Article Type
Original Article
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References

1. A Use Case in Smart Grid Communication Networks Browser Browser Attack and Deployment. 2024 IEEE Conference on Smart Grid
(Changde, China). GNU Zimmerman Homework Help Questions and Answers. SCADA Question and Answer. Homework help services
for Bachelor, Master, and Ph.D. students.
2. B. K. Sahu, R. D. Sharma and T. K. Das, "Deep Reinforcement Learning-based Cyberattack Detection in Smart Grids," IEEE Internet of
Things Journal, vol. 10, no. 8, pp. 6543-6555, Apr. 2023, doi: 10.1109/JIOT.2023.3245123
3. C. Wang, H. Yu and P. Chen, "Multi-Agent Systems for Distributed PMU Data Validation," Electric Power Systems Research, vol. 221,
Sept. 2023, pp. 109378, doi: 10.1016/j.epsr.2023.109378.
4. D. Patel and F. Liu, "Hybrid Edge-Cloud Framework for PMU Data Security," IEEE Access, vol. 11, pp. 78321-78335, Jul. 2023, doi:
10.1109/ACCESS.2023.3298412.
5. E. Rossi, J. Li and M. Hossain, "Graph Neural Network Based Anomaly Detection for Power Systems," IEEE Transactions on Power
Systems, vol. 39, no. 1, pp. 123-135, Jan. 2024, doi: 10.1109/TPWRS.2023.3312547.
6. F. Zhang, W. Yang and G. Wang, "Federated Learning for Real-Time PMU Data Analysis," IEEE Transactions on Industrial Informatics,
vol. 20, No. 4, pp. 4501-4513, Apr. 2024, doi: 10.1109/TII.2023.3337619.
7. G. Huang, S. Xu and L. Zhao, "Secure Data Aggregation in Smart Grids Using Homomorphic Encryption," IEEE Transactions on
Information Forensics and Security, vol. 19, pp. 234-246, Jan. 2024, doi: 10.1109/TIFS.2023.3329011.
8. We facilitate research and engagement on the fundamentals and practical aspects of the Smart Grid (SG) and its key technologies, such as
smart metering, asset management, fault detection, and the distribution, transmission, and dispatching of power in large-scale, cloud-
enabled networks.
9. I. Ahmed, L. Khan and R. Javaid, "PMU Assisted Situational Awareness in Distributed Energy Resources," IEEE Access, vol. 12, pp.
95612-95625, Oct. 2024, doi: 10.1109/ACCESS.2024.3435678.
10. J. Jiang, X. Liu, S. Wallace, E. Cotilla-Sanchez, R. Bass and X. Zhao, "Defending Against Adversarial Attacks in Transmission- and
Distribution-level PMU Data," arXiv preprint, Aug. 2020.
11. K. Shrestha, P. Kumar and D. Roy, "AI-Driven State Estimation and Fault Detection for Smart Grids," IEEE Transactions on Smart Grid,
vol. 15, no. 4, pp. 3224 - 3236, Jul. 2024, doi: 10.1109/TSG.2024.3356721.
12. L. A. Kumar, P. Patel and T. S. Mohan, "Cyber-Physical Anomaly Detection for Wide-Area Protection using PMU Data," arXiv preprint,
May 2023.
13. L. Zhang, X. Liu and Y. Wang, "Noise Resilient Learning for Attack Detection in Smart Grid PMU Data," IEEE Transactions on
Dependable and Secure Computing, vol. 21 no. 2, pp. 567-579, Feb. 2024, doi: 10.1109/TDSC.2023.3205678.
14. M. Hassan, P. Nguyen and D. Tran, "Blockchain-Based Secure PMU Data Management for Smart Grids," IEEE Access, vol. 12, pp. 65412
& 65426, Jun. 2024, doi: 10.1109/ACCESS.2024.338907
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