Study on the Early Warning of Three-phase Unbalance Online Monitoring Based on Data Mining

DOI

10.2991/meees-18.2018.14How to use a DOI?

Keywords

data mining, three-phase unbalance, urgent index.

Abstract

In the process of power system operation, three-phase unbalance has become normal. Based on the limitation of the filter rules on the three-phase unbalance, this article builds the discriminate model of it, firstly, eliminate abnormal data and restore the missing data through analyzing the real data distribution of three-phase unbalance ; then utilize the difference between the maximum phase current and the minimum phase current and study out a evaluation function on the urgent degree of three-phase unbalance, then qualitatively evaluate the urgent degree of reforming three-phase unbalance of different distribution transformer, and calculate its urgent index number. Based on these analyses, we can provide a more scientific and effective way of judging three-phase to guide the reform of unbalanced three-phase distribution transformer area for the workers in the power system.

Copyright

© 2018, 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  - Chen Gao
AU  - Zhong'an Ding
AU  - Wuxiao Chen
PY  - 2018/05
DA  - 2018/05
TI  - Study on the Early Warning of Three-phase Unbalance Online Monitoring Based on Data Mining
BT  - Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
PB  - Atlantis Press
SP  - 70
EP  - 74
SN  - 2352-5401
UR  - https://doi.org/10.2991/meees-18.2018.14
DO  - 10.2991/meees-18.2018.14
ID  - Gao2018/05
ER  -