Affiliations: [a] School of Artificial Intelligence, Bennett University, Greater Noida, U.P., India | [b] School of Computer Science Engineering and Technology, Bennett University, Greater Noida, U.P., India
Correspondence:
[*]
Corresponding author: Yajnaseni Dash, School of Artificial Intelligence, Bennett University, Greater Noida, U.P., India. E-mail: yajnasenidash@gmail.com.
Abstract: The optimal functioning of the power system is crucially dependent upon the sound protection of its major stakeholder, i.e., the transmission line, as it is prone to fault. To maintain the integrity of the power system and protect costly power system equipment, protective relaying is necessary to provide a steady and affordable supply of electricity. Relays recognize, classify, and identify transmission line faults using input signals of voltage and current. Many artificial intelligent methods based on Expert Systems, Artificial Neural Networks, Fuzzy Logic, Support Vector Machines, Wavelet-based systems, and deep learning techniques are being investigated to improve modern digital relays’ consistency, speed, and accuracy. This paper is a comprehensive and all-inclusive survey that reviews and incorporates Phasor Measurement Unit (PMU) and Global Positioning System (GPS) approaches together with all of these intelligent transmission line safety strategies and concepts. Initial investigators will benefit from this study by being able to examine, evaluate, and analyze a variety of approaches with references for all relevant contributions.
Keywords: Transmission line protection, expert system, Artificial Neural Network (ANN), Fuzzy Logic (FL), support vector machine, wavelet transform, deep learning
