Power quality event characterization

This paper presents an algorithm to characterize power quality (PQ) events. Any power quality event captured at the monitoring point will be analyzed automatically in three stages. The first stage differentiates between sag, swell or transient events by using wavelet analysis as well as time domain...

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Main Authors: Tan C.K., Kumaran V., Siam F.M., Busrah A.M.
Other Authors: 55921560400
Format: Conference paper
Published: 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-309712023-12-29T15:57:00Z Power quality event characterization Tan C.K. Kumaran V. Siam F.M. Busrah A.M. 55921560400 6602912020 26650164000 9742798900 Fault type classification Power quality Voltage sags Wavelet transform Zero sequence Animals Electric fault location Electric grounding Induction motors Power electronics Time domain analysis Underground cables Voltage stabilizing circuits Wavelet transforms Bus voltage Double line Fault location Fault type classification Ground faults Mitigation options Monitoring points Phase angle shift Power quality event Preventive measures Single line-to-ground faults Three stages Transformer energizing Transformer modeling Transient events Voltage sags Zero sequence Zero sequence voltage Electric measuring instruments This paper presents an algorithm to characterize power quality (PQ) events. Any power quality event captured at the monitoring point will be analyzed automatically in three stages. The first stage differentiates between sag, swell or transient events by using wavelet analysis as well as time domain analysis for counter checking purposes. Any sag events will automatically be passed to second stage to identify if the sag is caused by induction motor starting, transformer energizing or line faults. Important parameters such as phase angle shift, non/symmetrical sag, non/rectangular sag and sag duration are extracted and used for event characterization in the second stage. If a line fault is identified in the second stage, pseudo-measurement and transformer modeling will be executed to identify the fault location together with the 3-phase bus voltages at the faulted point. Here, the third stage is triggered and the line fault is further characterized into single line-to- ground fault, line-to-line fault or double line-to-ground fault by using the zero sequence voltage magnitude as well as zero sequence voltage angle. This automated event characterization algorithm provides a fast identification of areas that are prone to certain types of faults, which leads to much easier identification of causes of faults in that area - such as trees, animals, nature and etc. Preventive measures as well as the correct mitigation option can then be designed to reduce such incidences and thus improves power quality. Final 2023-12-29T07:57:00Z 2023-12-29T07:57:00Z 2008 Conference paper 10.1049/cp:20080580 2-s2.0-67449084066 https://www.scopus.com/inward/record.uri?eid=2-s2.0-67449084066&doi=10.1049%2fcp%3a20080580&partnerID=40&md5=1f7eac67336a08af6894814981180f7f https://irepository.uniten.edu.my/handle/123456789/30971 538 CP 543 547 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Fault type classification
Power quality
Voltage sags
Wavelet transform
Zero sequence
Animals
Electric fault location
Electric grounding
Induction motors
Power electronics
Time domain analysis
Underground cables
Voltage stabilizing circuits
Wavelet transforms
Bus voltage
Double line
Fault location
Fault type classification
Ground faults
Mitigation options
Monitoring points
Phase angle shift
Power quality event
Preventive measures
Single line-to-ground faults
Three stages
Transformer energizing
Transformer modeling
Transient events
Voltage sags
Zero sequence
Zero sequence voltage
Electric measuring instruments
spellingShingle Fault type classification
Power quality
Voltage sags
Wavelet transform
Zero sequence
Animals
Electric fault location
Electric grounding
Induction motors
Power electronics
Time domain analysis
Underground cables
Voltage stabilizing circuits
Wavelet transforms
Bus voltage
Double line
Fault location
Fault type classification
Ground faults
Mitigation options
Monitoring points
Phase angle shift
Power quality event
Preventive measures
Single line-to-ground faults
Three stages
Transformer energizing
Transformer modeling
Transient events
Voltage sags
Zero sequence
Zero sequence voltage
Electric measuring instruments
Tan C.K.
Kumaran V.
Siam F.M.
Busrah A.M.
Power quality event characterization
description This paper presents an algorithm to characterize power quality (PQ) events. Any power quality event captured at the monitoring point will be analyzed automatically in three stages. The first stage differentiates between sag, swell or transient events by using wavelet analysis as well as time domain analysis for counter checking purposes. Any sag events will automatically be passed to second stage to identify if the sag is caused by induction motor starting, transformer energizing or line faults. Important parameters such as phase angle shift, non/symmetrical sag, non/rectangular sag and sag duration are extracted and used for event characterization in the second stage. If a line fault is identified in the second stage, pseudo-measurement and transformer modeling will be executed to identify the fault location together with the 3-phase bus voltages at the faulted point. Here, the third stage is triggered and the line fault is further characterized into single line-to- ground fault, line-to-line fault or double line-to-ground fault by using the zero sequence voltage magnitude as well as zero sequence voltage angle. This automated event characterization algorithm provides a fast identification of areas that are prone to certain types of faults, which leads to much easier identification of causes of faults in that area - such as trees, animals, nature and etc. Preventive measures as well as the correct mitigation option can then be designed to reduce such incidences and thus improves power quality.
author2 55921560400
author_facet 55921560400
Tan C.K.
Kumaran V.
Siam F.M.
Busrah A.M.
format Conference paper
author Tan C.K.
Kumaran V.
Siam F.M.
Busrah A.M.
author_sort Tan C.K.
title Power quality event characterization
title_short Power quality event characterization
title_full Power quality event characterization
title_fullStr Power quality event characterization
title_full_unstemmed Power quality event characterization
title_sort power quality event characterization
publishDate 2023
_version_ 1806424260466442240