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Volume 4 Issue 3
May-June 2026
| Author(s) | Manish Nehare, Sheetal Bohrpee, Leeladhar Bisandre, Hivraj, Kapil Padlak |
|---|---|
| Country | India |
| Abstract | It has become increasingly challenging to ensure stability and reliability in electrical power systems. Although significant research and technological advancements have been made, a fast and accurate fault detection and classification technique is still needed to ensure security and reduce power outages caused by faults. With a rising population, the demand for electrical power has surged, leading to an increase in power generation units. These units are interconnected through a complex power system network. Malfunctions in the power system can result in significant electrical disruptions, which in turn may lead to substantial economic losses. Therefore, uninterruptible and reliable power transmission is essential to support the country’s economic activities. To maintain stability and improve reliability, accurate fault localisation is crucial. In real-life scenarios, faulty sections are isolated from healthy parts of the system using relays and circuit breakers, though relay activation may cause a slight delay. Machine learning (ML) models are trained using available data, such as fault voltage and fault current. Currently, research is focused on fault detection and classification using Deep Learning (DL) and ML techniques. |
| Keywords | Artificial Intelligence, Fault Detection, Power Restoration, Smart Grid, Machine Learning, Deep Learning. |
| Discipline | Engineering |
| Published In | Volume 4, Issue 3, May-June 2026 |
| Published On | 2026-05-12 |

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