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Islanding detection method using ridgelet probabilistic neural network in distributed generation

One of the challenging issues for a grid-connected embedded generation is to find a suitable technique to detect an islanding problem. The technique must be able to differentiate islanding from other grid disturbances and disconnect distributed generation (DG) rapidly to prevent from safety hazards,...

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Main Authors: Ahmadipour, Masoud, Hizam, Hashim, Othman, Mohammad Lutfi, Mohd Radzi, Mohd Amran
Format: Article
Language:English
Published: Elsevier 2019
Online Access:http://psasir.upm.edu.my/id/eprint/80331/1/Islanding%20detection%20method%20using%20ridgelet%20probabilistic%20neural%20network%20in%20distributed%20generation.pdf
http://psasir.upm.edu.my/id/eprint/80331/
https://www.sciencedirect.com/science/article/pii/S0925231218312499
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spelling my.upm.eprints.803312020-10-21T19:29:41Z http://psasir.upm.edu.my/id/eprint/80331/ Islanding detection method using ridgelet probabilistic neural network in distributed generation Ahmadipour, Masoud Hizam, Hashim Othman, Mohammad Lutfi Mohd Radzi, Mohd Amran One of the challenging issues for a grid-connected embedded generation is to find a suitable technique to detect an islanding problem. The technique must be able to differentiate islanding from other grid disturbances and disconnect distributed generation (DG) rapidly to prevent from safety hazards, power quality issues, equipment damage, as well as voltage and frequency instability. This study proposes a Slantlet transform as a signal processing method to extract the essential features to distinguish islanding from other disturbances. A ridgelet probabilistic neural network (RPNN) is utilized to classify islanding and grid disturbances. A modified differential evolution (MDF) algorithm with a new mutation phase, crossover process, and selection mechanism is proposed to train the RPNN. The results of the proposed technique show its capability and robustness to differentiate between islanding events and other grid disturbances Elsevier 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/80331/1/Islanding%20detection%20method%20using%20ridgelet%20probabilistic%20neural%20network%20in%20distributed%20generation.pdf Ahmadipour, Masoud and Hizam, Hashim and Othman, Mohammad Lutfi and Mohd Radzi, Mohd Amran (2019) Islanding detection method using ridgelet probabilistic neural network in distributed generation. Neurocomputing, 329 (15). pp. 188-209. ISSN 0925-2312 https://www.sciencedirect.com/science/article/pii/S0925231218312499 10.1016/j.neucom.2018.10.053
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description One of the challenging issues for a grid-connected embedded generation is to find a suitable technique to detect an islanding problem. The technique must be able to differentiate islanding from other grid disturbances and disconnect distributed generation (DG) rapidly to prevent from safety hazards, power quality issues, equipment damage, as well as voltage and frequency instability. This study proposes a Slantlet transform as a signal processing method to extract the essential features to distinguish islanding from other disturbances. A ridgelet probabilistic neural network (RPNN) is utilized to classify islanding and grid disturbances. A modified differential evolution (MDF) algorithm with a new mutation phase, crossover process, and selection mechanism is proposed to train the RPNN. The results of the proposed technique show its capability and robustness to differentiate between islanding events and other grid disturbances
format Article
author Ahmadipour, Masoud
Hizam, Hashim
Othman, Mohammad Lutfi
Mohd Radzi, Mohd Amran
spellingShingle Ahmadipour, Masoud
Hizam, Hashim
Othman, Mohammad Lutfi
Mohd Radzi, Mohd Amran
Islanding detection method using ridgelet probabilistic neural network in distributed generation
author_facet Ahmadipour, Masoud
Hizam, Hashim
Othman, Mohammad Lutfi
Mohd Radzi, Mohd Amran
author_sort Ahmadipour, Masoud
title Islanding detection method using ridgelet probabilistic neural network in distributed generation
title_short Islanding detection method using ridgelet probabilistic neural network in distributed generation
title_full Islanding detection method using ridgelet probabilistic neural network in distributed generation
title_fullStr Islanding detection method using ridgelet probabilistic neural network in distributed generation
title_full_unstemmed Islanding detection method using ridgelet probabilistic neural network in distributed generation
title_sort islanding detection method using ridgelet probabilistic neural network in distributed generation
publisher Elsevier
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/80331/1/Islanding%20detection%20method%20using%20ridgelet%20probabilistic%20neural%20network%20in%20distributed%20generation.pdf
http://psasir.upm.edu.my/id/eprint/80331/
https://www.sciencedirect.com/science/article/pii/S0925231218312499
_version_ 1681490816959250432
score 13.211869

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