Power Quality Analysis Using Frequency Domain Smooth - Windowed Wigner - Ville Distribution
Power quality has become a great concern to all electricity consumers. Poor power quality can cause equipment failure, data and economical losses. An automated monitoring system is needed to ensure signal quality, reduce diagnostic time and rectify failures. This paper presents the analysis of power...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
|
| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/20155/1/POWER%20QUALITY%20ANALYSIS%20USING%20FREQUENCY%20DOMAIN%20SMOOTH-WINDOWED%20WIGNER-VILLE%20DISTRIBUTION-ABDUL%20RAHIM%20ABDULLAH-MAK%2000330%20RAF.pdf http://eprints.utem.edu.my/id/eprint/20155/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Power quality has become a great concern to all electricity consumers. Poor power quality can cause equipment failure, data and economical losses. An automated monitoring system is needed to ensure signal quality, reduce diagnostic time and rectify failures. This paper presents the analysis of power quality signals using frequency domain smooth-windowed Wigner-Ville distribution (FDSWWVD). The power quality signals focused are swell, sag, interruption, harmonic, interharmonic and transient based on IEEE Std. 1159-2009. The TFD represents signal jointly in time-frequency representation (TFR) with good frequency and time resolution. Thus, it is very appropriate to analyze the signals that consist of multi-frequency components and magnitude variations. However, there is no fixed kernel of the TFD can be used to remove cross-terms for all types of signals. A set of performance measures is defined and used to compare the TFRs to identify and verify the TFD that operated at optimal kernel parameters. The result shows that FDSWWVD offers good performance of TFR and appropriate for power quality analysis. |
|---|