Detection of islanding and fault disturbances in microgrid using wavelet packet transform
Fast detection of islanding is very important for effective operation and control in distributed generation (DG) penetrated distribution networks. The islanding detection techniques such as passive, active, communication, and hybrid have their own merits and demerits. This paper proposed wavelet tra...
Saved in:
Main Authors: | , , , , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/150201 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-150201 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1502012021-05-20T01:53:06Z Detection of islanding and fault disturbances in microgrid using wavelet packet transform Ray, Prakash K. Panigrahi, Basanta K. Rout, Pravat K. Mohanty, Asit Foo, Eddy Yi Shyh Gooi, Hoay Beng School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Distributed Generation Fault and Islanding Fast detection of islanding is very important for effective operation and control in distributed generation (DG) penetrated distribution networks. The islanding detection techniques such as passive, active, communication, and hybrid have their own merits and demerits. This paper proposed wavelet transform (WT) and wavelet packet transform (WPT) based techniques for detection of islanding and fault disturbances in a microgrid consisting of resources like wind turbine generator, fuel cell (FC), and microturbine. Voltage signal is extracted at the point of common coupling (PCC) and is passed through these detection techniques to obtain the time-frequency multi-resolution analysis. Further, to validate the graphical study, performance indices (PIs) like standard deviation and entropy are calculated for the disturbance detection using suitable selection of threshold. A comparative analysis using WT and WPT is presented in the form of graphical simulation as well as in terms of PIs to analyse their effectiveness and robustness under different operating conditions. It is observed that WPT shows better detection capability in comparison to WT even under 20-dB noisy scenarios. National Research Foundation (NRF) Accepted version Authors acknowledge the support for research from the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. 2021-05-20T01:53:06Z 2021-05-20T01:53:06Z 2018 Journal Article Ray, P. K., Panigrahi, B. K., Rout, P. K., Mohanty, A., Foo, E. Y. S. & Gooi, H. B. (2018). Detection of islanding and fault disturbances in microgrid using wavelet packet transform. IETE Journal of Research, 65(6), 796-809. https://dx.doi.org/10.1080/03772063.2018.1454344 0377-2063 https://hdl.handle.net/10356/150201 10.1080/03772063.2018.1454344 2-s2.0-85046748714 6 65 796 809 en IETE Journal of Research © 2019 IETE. All rights reserved. This paper was published by Taylor & Francis in IETE Journal of Research and is made available with permission of IETE. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering::Electrical and electronic engineering Distributed Generation Fault and Islanding |
spellingShingle |
Engineering::Electrical and electronic engineering Distributed Generation Fault and Islanding Ray, Prakash K. Panigrahi, Basanta K. Rout, Pravat K. Mohanty, Asit Foo, Eddy Yi Shyh Gooi, Hoay Beng Detection of islanding and fault disturbances in microgrid using wavelet packet transform |
description |
Fast detection of islanding is very important for effective operation and control in distributed generation (DG) penetrated distribution networks. The islanding detection techniques such as passive, active, communication, and hybrid have their own merits and demerits. This paper proposed wavelet transform (WT) and wavelet packet transform (WPT) based techniques for detection of islanding and fault disturbances in a microgrid consisting of resources like wind turbine generator, fuel cell (FC), and microturbine. Voltage signal is extracted at the point of common coupling (PCC) and is passed through these detection techniques to obtain the time-frequency multi-resolution analysis. Further, to validate the graphical study, performance indices (PIs) like standard deviation and entropy are calculated for the disturbance detection using suitable selection of threshold. A comparative analysis using WT and WPT is presented in the form of graphical simulation as well as in terms of PIs to analyse their effectiveness and robustness under different operating conditions. It is observed that WPT shows better detection capability in comparison to WT even under 20-dB noisy scenarios. |
author2 |
School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Ray, Prakash K. Panigrahi, Basanta K. Rout, Pravat K. Mohanty, Asit Foo, Eddy Yi Shyh Gooi, Hoay Beng |
format |
Article |
author |
Ray, Prakash K. Panigrahi, Basanta K. Rout, Pravat K. Mohanty, Asit Foo, Eddy Yi Shyh Gooi, Hoay Beng |
author_sort |
Ray, Prakash K. |
title |
Detection of islanding and fault disturbances in microgrid using wavelet packet transform |
title_short |
Detection of islanding and fault disturbances in microgrid using wavelet packet transform |
title_full |
Detection of islanding and fault disturbances in microgrid using wavelet packet transform |
title_fullStr |
Detection of islanding and fault disturbances in microgrid using wavelet packet transform |
title_full_unstemmed |
Detection of islanding and fault disturbances in microgrid using wavelet packet transform |
title_sort |
detection of islanding and fault disturbances in microgrid using wavelet packet transform |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/150201 |
_version_ |
1701270611971538944 |