Aryan Singh
Independent Researcher
India
Abstract
The integration of the Internet of Things (IoT) in smart grid infrastructure has revolutionized the way utilities manage energy distribution, monitor asset health, and respond to faults. Traditional fault detection and isolation techniques are often constrained by latency, limited observability, and manual intervention. The evolution toward smart grids introduces intelligent devices, real-time data acquisition, and decentralized decision-making capabilities that are crucial for efficient fault localization and service restoration. This paper investigates the application of IoT technologies in enhancing fault detection and isolation (FDI) within smart grids. Through real-world case studies and methodological insights, the study evaluates how sensor networks, communication protocols, and AI-based analytics improve grid reliability and resilience. The paper also discusses architectural frameworks, result analysis, and practical implementations in diverse environments, with emphasis on grid automation, reduced outage durations, and proactive maintenance. Ultimately, the research contributes to the field by highlighting the potential and challenges of deploying IoT-enabled FDI mechanisms across various layers of the modern electric grid.
Keywords
Smart Grid, Fault Detection, Fault Isolation, IoT Sensors, Grid Automation, Energy Systems, Real-time Monitoring, Distribution Networks, Predictive Maintenance
REFERENCES
- Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2013). Smart grid technologies: Communication technologies and standards. IEEE Transactions on Industrial Informatics, 7(4), 529–539. https://doi.org/10.1109/TII.2011.2166794
- Yan, Y., Qian, Y., Sharif, H., & Tipper, D. (2013). A survey on smart grid communication infrastructures: Motivations, requirements and challenges. IEEE Communications Surveys & Tutorials, 15(1), 5–20. https://doi.org/10.1109/SURV.2012.021312.00034
- Yu, R., Zhang, Y., Gjessing, S., Xia, W., & Yang, K. (2013). Cognitive radio based hierarchical communications infrastructure for smart grid. IEEE Network, 25(5), 6–14. https://doi.org/10.1109/MNET.2011.6051119
- Fang, X., Misra, S., Xue, G., & Yang, D. (2012). Smart grid – The new and improved power grid: A survey. IEEE Communications Surveys & Tutorials, 14(4), 944–980. https://doi.org/10.1109/SURV.2011.101911.00087
- Gharavi, H., & Ghafurian, R. (2011). Smart grid: The electric energy system of the future. Proceedings of the IEEE, 99(6), 917–921. https://doi.org/10.1109/JPROC.2011.2114630
- Liu, C., Phadke, A. G., Thorp, J. S., & Centeno, V. (2012). Power system state estimation using PMUs and SCADA measurements. IEEE Transactions on Smart Grid, 3(3), 1501–1509. https://doi.org/10.1109/TSG.2012.2196679
- Rehmani, M. H., Reisslein, M., Rachedi, A., Erol-Kantarci, M., & Radenkovic, M. (2018). Integrating renewable energy resources into the smart grid: Recent developments in information and communication technologies. IEEE Transactions on Industrial Informatics, 14(7), 2814–2825. https://doi.org/10.1109/TII.2018.2819169
- Galli, S., Scaglione, A., & Wang, Z. (2011). For the grid and through the grid: The role of power line communications in the smart grid. Proceedings of the IEEE, 99(6), 998–1027. https://doi.org/10.1109/JPROC.2011.2109670
- Ahmed, R., & Rehmani, M. H. (2017). Mobile edge computing for IoT applications in smart homes. IEEE Access, 5, 8472–8489. https://doi.org/10.1109/ACCESS.2017.2694184
