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A Review Paper Of Artificial Intelligence-Based Power Fault Detection and Power Restoration

Author(s) Prof. Kapil Padlak, Manish Nehare, Sheetal Bohrpee
Country India
Abstract It has become increasingly challenging to ensure stability and maintain 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 localization is crucial. In real-life scenarios, faulty sections are isolated from healthy parts of the system with the help of relays and circuit breakers, though relay activation may incur 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.
Field Engineering
Published In Volume 6, Issue 11, November 2025
Published On 2025-11-21
Cite This A Review Paper Of Artificial Intelligence-Based Power Fault Detection and Power Restoration - Prof. Kapil Padlak, Manish Nehare, Sheetal Bohrpee - IJLRP Volume 6, Issue 11, November 2025.
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