Classification and Identification of Voltage Sag Sources in Distribution Network with Harmonic

DOI

10.2991/icmemtc-16.2016.335How to use a DOI?

Keywords

harmonic; voltage sag source; EMD Energy Entropy; probability neural network(PNN)

Abstract

A new method to identify voltage sag sources in power distribution network with harmonic is proposed, this method use the theory of EMD to decompose the voltage signals, and obtain a series of IMF. For different voltage sag sources, the IMF's complexities are not the same, so the concept of the EMD energy entropy character is proposed to measure these complexities. The analysis results show that the EMD energy entropy of three-phase voltage for transformer energization is largest; the single phase grounding fault is second; the induction motor starting is minimum, and is close to the normal voltage signals. Finally, combing with PNN to classify and identify voltage sag sources in power distribution network with harmonic, lots of simulation results show that the proposed method in this paper has a high accuracy, and is significantly better than BPNN classifier.

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  - Yajuan Liu
AU  - Wu Zhu
PY  - 2016/04
DA  - 2016/04
TI  - Classification and Identification of Voltage Sag Sources in Distribution Network with Harmonic
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 1773
EP  - 1780
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.335
DO  - 10.2991/icmemtc-16.2016.335
ID  - Liu2016/04
ER  -