Advanced techniques for fault detection and classification in electrical power transmission systems: An overview

One of the consequences of the power systems complexity increasing consists in the rise of probability of system fault occurrence. A rapid restoration of power system enhances the service reliability and reduces power outages; therefore, fault section should be estimated quickly and accurately. Transmission lines, as important elements of power systems, may be subject to unexpected failures due to various faults. So, to guarantee the reliability and safety of a power system, efficient fault detection, classification and localization (FDL) schemes for transmission lines are essential. Consequently, the improvement in suitable techniques for the fault detection and classification (FD) in power transmission systems, to increase the efficiency of the systems and to avoid major damages, it is a permanent requirement. A lot of FD methods are described in the technical literature and proposed by a large variety of research works, so a suitable survey of these methods is needed for choosing the most proper FD technique. In this work, an overview on the methods used for FD in transmission systems is accomplished, analyzing the technical literature and summarizing the most important methods that can be applied for FD. After overall concepts and general ideas are presented, representative works are covered and discussed briefly, focusing on the newly approaches (including machine learning) developed by various researchers for FD in power transmission systems.