Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6860358 | International Journal of Electrical Power & Energy Systems | 2014 | 11 Pages |
Abstract
Results and Conclusions: To verify the effectiveness of the proposed scheme, extensive simulations have been carried out under different fault conditions with wide variations in fault type, fault resistance, fault location and fault inception angle. Simulations results show that the proposed scheme is faster and more accurate than the back-propagation neural network (BPNN), and it is proved to be a robust classifier for digital protection.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zhengyou He, Sheng Lin, Yujia Deng, Xiaopeng Li, Qingquan Qian,