Mono ANN Module Protection Scheme and Multi ANN Modules for Fault Location Estimation for a Six-Phase Transmission Line Using Discrete Wavelet Transform
Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JOAPE-12-4_006
تاریخ نمایه سازی: 28 بهمن 1402
Abstract:
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 ۱۲۰ types of different possible short circuit faults. This work presents a protection scheme with discrete wavelet transform (db۴ 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 ۱۲۰ fault types, a single ANN module is implemented with six inputs and six outputs. For fault location estimation in each phase, ۱۱ ANN modules with six outputs are implemented, one for each of the ۱۱ 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 ۹۹.۷۶%. It is found that the performance of the fault location estimation modules is better with the training data and moderate with the testing data.
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Authors
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
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