Detection and identification of fault in transmission lines based on ANN
More details
Hide details
Northern Technical University
Submission date: 2023-11-29
Final revision date: 2024-03-06
Acceptance date: 2024-03-11
Online publication date: 2024-03-14
Publication date: 2024-03-14
Corresponding author
Ahmed Ghazi Abdullah   

Northern Technical University
Along with power transmission lines' efficiency, another crucial factor in electrical power transmission networks is reliability, which guarantees power transmission stability. One of the crucial and essential tasks for maintaining the continuity and stability of power transmission in transmission networks Capacity without any significant failures is identifying errors and malfunctions in power transmission lines as soon as possible. The goal of this article is to develop and apply ANN technology to overcome the obstacles faced by the electrical power transmission network. In order for the ANN to learn useful patterns and features from raw current measurements, pre-processing and feature extraction techniques are used during the training process. Real-time applications can benefit from the ANN's architecture, which is optimized for high accuracy, quick response times, and scalability. To validate the performance of the ANN-based fault detection system, extensive simulations are conducted using data from different transmission line scenarios, including various fault types that short-circuit. The results demonstrate the capability of the ANN model to accurately detect and classify faults, as well as disconnect the power grid after detect any fault. The results showed the accuracy and high speed of the proposed method using a neural network compared to traditional methods.
This research received no external funding.
Thwe EP, Oo MM. Fault Detection and Classification for Transmission Line Protection System Using Artificial Neural Network. Journal of Electrical and Electronic Engineering 2016; 4(5): 89–96.
Abdulwahid Salman M, Muhammad Ali S. ANN Based Detection and Location of Severe Three Phase Trip on the Transmission Lines of an Uncontrolled Power System.
Pandey A, Gadekar P, Khadse C. Artificial Neural Network based Fault Detection System for 11 kV Transmission Line. 2021.
Karupiah S, Hussain MH, Musirin I, Rahim SRA. Prediction of overcurrent rRelay miscoordination time using artificial neural network. Indonesian Journal of Electrical Engineering and Computer Science 2019; 14(1): 319–26.
Baseer MA. Travelling Waves for Finding the Fault Location in Transmission Lines. Journal of Electrical and Electronic Engineering 2013; 1(1): 1–19.
Goad S, Yadav A. Fault Detection on Transmission Lines Using Artificial Neural Network n.d.
Padney A, Gadekar PS, Khadse CB. (2021). Artificial Neural Network based Fault Detection System for 11 kV Transmission Line. 2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) 2021; 1-4.
Touati KOM, Boudiaf M, Merzouk I, Hafaifa A. Intelligent fault diagnosis of power transmission line using fuzzy logic and artificial neural network. Diagnostyka 2022; 23(4).
Zhang Q, Ma W, Li G, Ding J, Xie M. Fault diagnosis of power grid based on variational mode decomposition and convolutional neural network. Electric Power Systems Research 2022; 208: 107871.
Chowdary KY, Kumar S. Detection, Location, and Classification of Fault Applying Artificial Neural Networks in Power System Transmission Line. 2022 IEEE International Conference on Current Development in Engineering and Technology (CCET) 2022; 1–6.
Firos A, Prakash N, Gorthi R, Soni M, Kumar S, Balaraju V. Fault detection in power transmission lines using AI model. 2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS). 2023.
Kumari S, Mishra A, Singhal A, Dahiya V, Gupta M, Gawre SK. Fault Detection in Transmission Line Using ANN. 2023 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS) 2023; 1–5.
Idris R, Lim NA. Optimal Methods for Fault Detection and Classification. ELEKTRIKA- Journal of Electrical Engineering 2023; 22(1): 75–82.
Tayeb EBM, Rhim OAAA. Transmission line faults detection, classification and location using artificial neural network. 2011 International Conference & Utility Exhibition on Power and Energy Systems: Issues and Prospects for Asia (ICUE) 2011 s. 1–5.
Islam MS, Kabir MM. ANN Based Discrimination of Inrush and Fault Currents in Three Phase Power Transformer using Statistical Approaches. 2019 4th International Conference on Electrical Information and Communication Technology, EICT 2019; 20–2.
Parmar MSB. Transformer protection using artificial neural network. IJNRD-International Journal of Novel Research and Development (IJNRD) 2017; 2: 108–11.
Ali E, Helal A, Desouki H, Shebl K, Abdelkader S, Malik OP. Power transformer differential protection using current and voltage ratios. Electric Power Systems Research 2018; 154: 140–50.
Journals System - logo
Scroll to top