Prajwal A Sontakke
Dr. R. B. Sharma
Abstract
Transmission lines are an essential component of the power system network, serving as a critical link in the country’s energy system by transferring enormous amounts of electricity at high voltages from producing stations to substations. With an ever-growing demand for electric power as a result of increased industrialization and urbanization, quick and accurate fault investigation is critical for better performance as well as fewer outages in power sector. To be fault-free, transmission lines require real-time monitoring and quick control. The categorization and detection of faulty conditions in power systems has evolved into a critical task. This study provides an in-depth examination of several algorithms that have been developed and deployed in recent years for the categorization and detection of faults in transmission lines.
Keywords- Artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS), Fault Categorization, Fault Detection, Machine Learning, Power System, Support Vector Machine (SVM)