Fault classification on transmission line of 10kV rural power grid

DOI

10.2991/icsmim-15.2016.72How to use a DOI?

Keywords

Discrete Wavelet Transform, Neural Network, Transmission Line, Fault Classification,PSCAD

Abstract

This paper proposes a technique using Discrete Wavelet Transform (DWT) and Back-Propagation Neural Network (BPNN) to identify the fault types on transmission line of 10kv rural power grid. The PSCAD is used to simulate fault signals. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. The variations of first scale high frequency component that detect fault are used as an input for the training pattern. The result has shown that the proposed technique gives satisfactory results

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chunyu Lv
AU  - Shuguang Zhang
PY  - 2016/01
DA  - 2016/01
TI  - Fault classification on transmission line of 10kV rural power grid
BT  - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
PB  - Atlantis Press
SP  - 384
EP  - 387
SN  - 2352-538X
UR  - https://doi.org/10.2991/icsmim-15.2016.72
DO  - 10.2991/icsmim-15.2016.72
ID  - Lv2016/01
ER  -