Research Article
An Artificial Neural Network Based Digital Differential Protection Scheme for Synchronous Generator Stator Winding Protection
@ARTICLE{10.4108/eai.30-1-2019.160837, author={Muhammad Faisal Riaz and Fawwad Hassan Jaskani and Tehreem Awan}, title={An Artificial Neural Network Based Digital Differential Protection Scheme for Synchronous Generator Stator Winding Protection}, journal={EAI Endorsed Transactions on Creative Technologies}, volume={6}, number={18}, publisher={EAI}, journal_a={CT}, year={2019}, month={1}, keywords={ANN, Winding Protection, Neural Networks}, doi={10.4108/eai.30-1-2019.160837} }- Muhammad Faisal Riaz
Fawwad Hassan Jaskani
Tehreem Awan
Year: 2019
An Artificial Neural Network Based Digital Differential Protection Scheme for Synchronous Generator Stator Winding Protection
CT
EAI
DOI: 10.4108/eai.30-1-2019.160837
Abstract
This research depicts another artificial neural network (ANN) based digital differential protection scheme for generator stator winding protection. The scheme incorporates two feedforward neural networks (FNNs). One ANN is utilized for flaw recognition and the other is utilized for inward deficiency grouping. This structure utilizes current examples from the line-side and the unbiased end notwithstanding tests from the field current. Essential and/or second consonant present in the field current during an issue help the ANN, utilized for flaw location, to separate between generator states (typical, outside issue and interior deficiency states). Results demonstrating the performance of the protection scheme are displayed and show that it is quick and solid.
Copyright © 2019 Muhammad Faisal Riaz et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
