In recent years, with the widely application of power electronic devices and stringent requirement of industrial process, voltage sag has caused much attention in many countries. To design effective and efficient mitigation and management strategies, it is essential to have accurate classification of voltage sag sources. In this paper, based on the analysis of massive voltage sag events in the grid recorded by online power quality monitoring systems in several different regions in China, a more extensive and practical classification of voltage sag sources is given. The voltage sags are divided into eight categories due to short circuit faults with symmetric and asymmetric faults included, transformer energizing, induction motor starting, lightning faults, self-extinguishing faults, the combined action of short circuit faults and heavy load starting, upgrade faults and multistage voltage sags. For each category of the voltage sag sources, both the instantaneous value and the root mean square (RMS) value of the waveform of the typical recorded events are given. In addition, the reasons are analysed and the waveform characteristics are summarized for each category of the voltage sag sources. Finally, the frequencies of eight categories under different voltage levels and the statistical result analysis are given.
[1]
E. Styvaktakis,et al.
Expert System for Classification and Analysis of Power System Events
,
2002,
IEEE Power Engineering Review.
[2]
Irene Yu-Hua Gu,et al.
Classification of power system events: voltage dips
,
2000,
Ninth International Conference on Harmonics and Quality of Power. Proceedings (Cat. No.00EX441).
[3]
Bo Zhou,et al.
An expert system based on s-transform for classification of voltage dips
,
2011,
2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC).
[4]
Sukumar Mishra,et al.
Detection and classification of voltage sag causes based on empirical mode decomposition
,
2011,
2011 Annual IEEE India Conference.
[5]
Ning Wang,et al.
The method to reduce identification feature of different voltage sag disturbance source based on principal component analysis
,
2014
.
[6]
Yixuan Wang,et al.
Voltage sag source location technology based on corresponding sequence components
,
2015
.
[7]
Kevin Barraclough,et al.
I and i
,
2001,
BMJ : British Medical Journal.
[8]
W. Marsden.
I and J
,
2012
.
[9]
Neil Genzlinger.
A. and Q
,
2006
.