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Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile / Alvaro Furlani Bastos; Walmir Freitas; Grazia Todeschini; Surya Santoso

IET Generation, Transmission & Distribution

Swansea University Author: Grazia, Todeschini

Abstract

Power quality disturbances commonly observed in power systems have been studied for decades, resulting in numerous algorithms for detecting the events that affect the voltage and/or current waveforms. However, a considerable amount of disturbances is not visually observable in the raw waveforms, esp...

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Published in: IET Generation, Transmission & Distribution
ISSN: 1751-8687 1751-8695
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa49809
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first_indexed 2019-03-29T12:39:44Z
last_indexed 2020-09-11T03:11:39Z
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spelling 2020-09-10T08:52:25.3941634 v2 49809 2019-03-29 Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile c4ff9050b31bdec0e560b19bfb3b56d3 0000-0001-9411-0726 Grazia Todeschini Grazia Todeschini true false 2019-03-29 EEN Power quality disturbances commonly observed in power systems have been studied for decades, resulting in numerous algorithms for detecting the events that affect the voltage and/or current waveforms. However, a considerable amount of disturbances is not visually observable in the raw waveforms, especially switching operations. These events must be detected through an alternative feature, such as abrupt variations in the root-mean-square (rms) voltage profile. This study examines the methods commonly used for detecting power quality disturbances in the waveform or rms voltage profile domains and identifies their limitations. Afterwards, a novel step change detector is proposed based on a modified median filter and rms voltage gradient values to overcome the deficiencies of the existing methods. The effectiveness of the proposed method is assessed by applying it to both simulated and field data. This assessment shows that the method detects all switching events with no false positives for the datasets under analysis. Journal Article IET Generation, Transmission & Distribution 1751-8687 1751-8695 31 12 2019 2019-12-31 10.1049/iet-gtd.2018.6511 COLLEGE NANME Engineering COLLEGE CODE EEN Swansea University 2020-09-10T08:52:25.3941634 2019-03-29T09:52:52.9215732 Alvaro Furlani Bastos 1 Walmir Freitas 2 Grazia Todeschini 0000-0001-9411-0726 3 Surya Santoso 4 0049809-24042019145512.pdf bastos2019v2.pdf 2019-04-24T14:54:08.6670000 Output 6855594 application/pdf Accepted Manuscript true 2019-04-23T00:00:00.0000000 true eng
title Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile
spellingShingle Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile
Grazia, Todeschini
title_short Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile
title_full Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile
title_fullStr Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile
title_full_unstemmed Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile
title_sort Detection of Inconspicuous Power Quality Disturbances through Step Changes in rms Voltage Profile
author_id_str_mv c4ff9050b31bdec0e560b19bfb3b56d3
author_id_fullname_str_mv c4ff9050b31bdec0e560b19bfb3b56d3_***_Grazia, Todeschini
author Grazia, Todeschini
author2 Alvaro Furlani Bastos
Walmir Freitas
Grazia Todeschini
Surya Santoso
format Journal article
container_title IET Generation, Transmission & Distribution
publishDate 2019
institution Swansea University
issn 1751-8687
1751-8695
doi_str_mv 10.1049/iet-gtd.2018.6511
document_store_str 1
active_str 0
description Power quality disturbances commonly observed in power systems have been studied for decades, resulting in numerous algorithms for detecting the events that affect the voltage and/or current waveforms. However, a considerable amount of disturbances is not visually observable in the raw waveforms, especially switching operations. These events must be detected through an alternative feature, such as abrupt variations in the root-mean-square (rms) voltage profile. This study examines the methods commonly used for detecting power quality disturbances in the waveform or rms voltage profile domains and identifies their limitations. Afterwards, a novel step change detector is proposed based on a modified median filter and rms voltage gradient values to overcome the deficiencies of the existing methods. The effectiveness of the proposed method is assessed by applying it to both simulated and field data. This assessment shows that the method detects all switching events with no false positives for the datasets under analysis.
published_date 2019-12-31T04:09:56Z
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score 10.751122