University of Mohaghegh Ardabili Journal of Operation and Automation in Power Engineering 2322-4576 12 4 2024 12 01 Mono ANN Module Protection Scheme and Multi ANN Modules for Fault Location Estimation for a Six-Phase Transmission Line Using Discrete Wavelet Transform طرح حفاظت از ماژول ANN مونو و ماژول های چندگانه ANN برای تخمین مکان خطا برای یک خط انتقال شش فاز با استفاده از تبدیل موجک گسسته 337 351 2294 10.22098/joape.2023.11690.1874 EN G. Vikram Raju Department of Electrical Engineering, National Institute of Technology, Warangal, India N. Venkata Srikanth Department of Electrical Engineering, National Institute of Technology, Warangal, India Journal Article 2022 10 18 The enhanced power transfer capability is possible with the six-phase transmission system but it did not gain popularity due to the lack of a proper protection scheme to secure the line from 120 types of different possible short circuit faults. This work presents a protection scheme with discrete wavelet transform (db4 mother wavelet) and an artificial neural network (ANN). The Levenberg-Marquardt algorithm is used for training the ANNs. This protection scheme requires only the pre-processed current information of the sending end bus. For fault detection and classification of all 120 fault types, a single ANN module is implemented with six inputs and six outputs. For fault location estimation in each phase, 11 ANN modules with six outputs are implemented, one for each of the 11 types of combination of faults. The MATLAB/ SIMULINK simulation results of the proposed protection technique implemented on the six-phase Allegheny power transmission system show that it is effective and efficient in detecting and classifying all the faults with varying fault parameters with an accuracy of 99.76%. It is found that the performance of the fault location estimation modules is better with the training data and moderate with the testing data. https://joape.uma.ac.ir/article_2294_e6277933e3ae5bfa7da7f4726e720286.pdf