Cover Image

A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam

One of the main requirements of distribution utility companies related to interconnection of distributed generation (DG) is islanding detection technique. Islanding occurs when part of the distribution system becomes electrically isolated from the main supply, and it remains energized by DG in an is...

Full description

Saved in:
Bibliographic Details
Main Author: Ab Salam, Aimie Nadia
Format: Thesis
Language:English
Published: 2019
Online Access:https://ir.uitm.edu.my/id/eprint/84239/1/84239.pdf
https://ir.uitm.edu.my/id/eprint/84239/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.84239
record_format eprints
spelling my.uitm.ir.842392024-07-30T07:03:34Z https://ir.uitm.edu.my/id/eprint/84239/ A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam Ab Salam, Aimie Nadia One of the main requirements of distribution utility companies related to interconnection of distributed generation (DG) is islanding detection technique. Islanding occurs when part of the distribution system becomes electrically isolated from the main supply, and it remains energized by DG in an isolated subsystem. Failure to detect islanding may lead to power quality issues, equipment damage and safety issues concerning the electrical company workers. Therefore, DG connection codes worldwide require that all islanded DGs to be disconnected as fast as possible after the formation of islanding. Among islanding detection technique, computational intelligence technique is the most recent approach that can produce almost zero nondetection zone. The objective of this thesis is to design a new islanding detection technique for synchronous type of DG based on the most sensitive passive parameters by using Artificial Neural Network (ANN) Evolutionary Programming (EP). The most sensitive parameter is selected from the sixteen parameters designated for this study considering the sensitivity analysis. The analysis is produced based on the response of each parameter when the test system is subjected with different types of islanding and non-islanding event. 2019 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/84239/1/84239.pdf A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam. (2019) Masters thesis, thesis, Universiti Teknologi MARA (UiTM). <http://terminalib.uitm.edu.my/84239.pdf>
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description One of the main requirements of distribution utility companies related to interconnection of distributed generation (DG) is islanding detection technique. Islanding occurs when part of the distribution system becomes electrically isolated from the main supply, and it remains energized by DG in an isolated subsystem. Failure to detect islanding may lead to power quality issues, equipment damage and safety issues concerning the electrical company workers. Therefore, DG connection codes worldwide require that all islanded DGs to be disconnected as fast as possible after the formation of islanding. Among islanding detection technique, computational intelligence technique is the most recent approach that can produce almost zero nondetection zone. The objective of this thesis is to design a new islanding detection technique for synchronous type of DG based on the most sensitive passive parameters by using Artificial Neural Network (ANN) Evolutionary Programming (EP). The most sensitive parameter is selected from the sixteen parameters designated for this study considering the sensitivity analysis. The analysis is produced based on the response of each parameter when the test system is subjected with different types of islanding and non-islanding event.
format Thesis
author Ab Salam, Aimie Nadia
spellingShingle Ab Salam, Aimie Nadia
A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam
author_facet Ab Salam, Aimie Nadia
author_sort Ab Salam, Aimie Nadia
title A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam
title_short A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam
title_full A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam
title_fullStr A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam
title_full_unstemmed A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam
title_sort new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / aimie nadia ab salam
publishDate 2019
url https://ir.uitm.edu.my/id/eprint/84239/1/84239.pdf
https://ir.uitm.edu.my/id/eprint/84239/
_version_ 1806454649829457920
score 13.211869

Similar Items