Open AccessVoltage sag/swell waveform analysis method based on multi‐dimension characterisation
Author(s) -
Hu WenXi,
Xiao XianYong,
Zheng ZiXuan
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.1038
Subject(s) - waveform , voltage sag , voltage , dimension (graph theory) , computer science , swell , segmentation , filter (signal processing) , electronic engineering , control theory (sociology) , power quality , engineering , mathematics , artificial intelligence , electrical engineering , computer vision , physics , pure mathematics , control (management) , thermodynamics
Voltage magnitude and sag duration are known as acknowledged basic voltage sag characteristics in the last decades. However, these values cannot meet the demands of waveform analysis in the modern smart grid. Therefore, voltage sag multi‐dimension characterisation is required to extract more essential information from measured waveforms. This study focuses on the unsolved issue that how to obtain required characteristics from voltage sag waveforms effectively. Overall, multi‐dimension characterisation method contains several parts: voltage sag detection, segmentation and characteristics calculation. Fundamental voltage magnitude and phase angle, obtained by the proposed adaptive generalised morphology filter, are segmented in several parts. Then, a set of characteristics are calculated to characterise the voltage sag waveform in a multi‐dimensional way. Performance of the proposed method is validated by synthetic and measured waveforms. Results show that both detection and segmentation methods have better performance than existing typical methods, and multi‐dimension characteristics can be extracted from waveforms accurately. Moreover, the proposed method can be implemented in power quality monitoring system to support further sag studies.