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Smart Grid Fault Mitigation and Cybersecurity with Wide-Area Measurement Systems: A Review

Author

Listed:
  • Chisom E. Ogbogu

    (College of Engineering, Carnegie Mellon University Africa, Kigali BP 6150, Rwanda)

  • Jesse Thornburg

    (College of Engineering, Carnegie Mellon University Africa, Kigali BP 6150, Rwanda
    Grid Fruit, LLC., Austin, TX 78758, USA)

  • Samuel O. Okozi

    (Department of Electrical Engineering, School of Electrical Systems and Engineering Technology, Federal University of Technology Owerri, Owerri PMB 1526, Nigeria)

Abstract

Smart grid reliability and efficiency are critical for uninterrupted service, especially amidst growing demand and network complexity. Wide-Area Measurement Systems (WAMS) are valuable tools for mitigating faults and reducing fault-clearing time while simultaneously prioritizing cybersecurity. This review looks at smart grid WAMS implementation and its potential for cyber-physical power system (CPPS) development and compares it to traditional Supervisory Control and Data Acquisition (SCADA) infrastructure. While traditionally used in smart grids, SCADA has become insufficient in handling modern grid dynamics. WAMS differ through utilizing phasor measurement units (PMUs) to provide real-time monitoring and enhance situational awareness. This review explores PMU deployment models and their integration into existing grid infrastructure for CPPS and smart grid development. The review discusses PMU configurations that enable precise measurements across the grid for quicker, more accurate decisions. This study highlights models of PMU and WAMS deployment for conventional grids to convert them into smart grids in terms of the Smart Grid Architecture Model (SGAM). Examples from developing nations illustrate cybersecurity benefits in cyber-physical frameworks and improvements in grid stability and efficiency. Further incorporating machine learning, multi-level optimization, and predictive analytics can enhance WAMS capabilities by enabling advanced fault prediction, automated response, and multilayer cybersecurity.

Suggested Citation

  • Chisom E. Ogbogu & Jesse Thornburg & Samuel O. Okozi, 2025. "Smart Grid Fault Mitigation and Cybersecurity with Wide-Area Measurement Systems: A Review," Energies, MDPI, vol. 18(4), pages 1-26, February.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:994-:d:1594203
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    References listed on IDEAS

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    1. Abdulaziz Almalaq & Saleh Albadran & Amer Alghadhban & Tao Jin & Mohamed A. Mohamed, 2022. "An Effective Hybrid-Energy Framework for Grid Vulnerability Alleviation under Cyber-Stealthy Intrusions," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
    2. Shi, Zhongtuo & Yao, Wei & Li, Zhouping & Zeng, Lingkang & Zhao, Yifan & Zhang, Runfeng & Tang, Yong & Wen, Jinyu, 2020. "Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions," Applied Energy, Elsevier, vol. 278(C).
    3. Chinmayee Biswal & Binod Kumar Sahu & Manohar Mishra & Pravat Kumar Rout, 2023. "Real-Time Grid Monitoring and Protection: A Comprehensive Survey on the Advantages of Phasor Measurement Units," Energies, MDPI, vol. 16(10), pages 1-34, May.
    4. Rouhani, Seyed Hossein & Su, Chun-Lien & Mobayen, Saleh & Razmjooy, Navid & Elsisi, Mahmoud, 2024. "Cyber resilience in renewable microgrids: A review of standards, challenges, and solutions," Energy, Elsevier, vol. 309(C).
    5. Zhao Song & Christoph M. Hackl & Abhinav Anand & Andre Thommessen & Jonas Petzschmann & Omar Kamel & Robert Braunbehrens & Anton Kaifel & Christian Roos & Stefan Hauptmann, 2023. "Digital Twins for the Future Power System: An Overview and a Future Perspective," Sustainability, MDPI, vol. 15(6), pages 1-29, March.
    6. Dileep, G., 2020. "A survey on smart grid technologies and applications," Renewable Energy, Elsevier, vol. 146(C), pages 2589-2625.
    7. MacMatthew C. Ahaotu & Chisom E. Ogbogu & Jesse Thornburg & Isdore Onyema Akwukwaegbu, 2025. "Simulation of PEM Electrolyzer Power Management with Renewable Generation in Owerri, Nigeria," Energies, MDPI, vol. 18(1), pages 1-23, January.
    8. Abdulaziz Almalaq & Saleh Albadran & Mohamed A. Mohamed, 2022. "Deep Machine Learning Model-Based Cyber-Attacks Detection in Smart Power Systems," Mathematics, MDPI, vol. 10(15), pages 1-16, July.
    9. Mojgan Hojabri & Ulrich Dersch & Antonios Papaemmanouil & Peter Bosshart, 2019. "A Comprehensive Survey on Phasor Measurement Unit Applications in Distribution Systems," Energies, MDPI, vol. 12(23), pages 1-23, November.
    10. Paolo Sospiro & Lohith Amarnath & Vincenzo Di Nardo & Giacomo Talluri & Foad H. Gandoman, 2021. "Smart Grid in China, EU, and the US: State of Implementation," Energies, MDPI, vol. 14(18), pages 1-16, September.
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