An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique
The purpose of planned islanding is to construct a power island during system disturbances which are commonly formed for maintenance purpose. However, in most of the cases island mode operation is not allowed. Therefore distributed generators (DGs) must sense the unplanned disconnection from the...
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my.utem.eprints.94732015-05-28T04:04:17Z http://eprints.utem.edu.my/id/eprint/9473/ An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique Khamis, Aziah TK Electrical engineering. Electronics Nuclear engineering The purpose of planned islanding is to construct a power island during system disturbances which are commonly formed for maintenance purpose. However, in most of the cases island mode operation is not allowed. Therefore distributed generators (DGs) must sense the unplanned disconnection from the main grid. Passive technique is the most commonly used method for this purpose. However, it needs improvement in order to identify the islanding condition. In this paper an effective method for identification of islanding condition based on phase space and neural network techniques has been developed. The captured voltage waveforms at the coupling points of DGs are processed to extract the required features. For this purposed a method known as the phase space techniques is used. Based on extracted features, two neural network configuration namely radial basis function and probabilistic neural networks are trained to recognize the waveform class. According to the test result, the investigated technique can provide satisfactory identification of the islanding condition in the distribution system. WASET 2013-07-27 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/9473/1/v78-208%28aziah_waset%29.pdf Khamis, Aziah (2013) An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique. World Academy of Science, Engineering and Technology 78 2013, 78. pp. 1221-1229. ISSN (p-ISSN : 2010-376X ; e-ISSN : 2010-3778) |
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The purpose of planned islanding is to construct a
power island during system disturbances which are commonly
formed for maintenance purpose. However, in most of the cases
island mode operation is not allowed. Therefore distributed
generators (DGs) must sense the unplanned disconnection from the
main grid. Passive technique is the most commonly used method for
this purpose. However, it needs improvement in order to identify the
islanding condition. In this paper an effective method for
identification of islanding condition based on phase space and neural
network techniques has been developed. The captured voltage
waveforms at the coupling points of DGs are processed to extract the
required features. For this purposed a method known as the phase
space techniques is used. Based on extracted features, two neural
network configuration namely radial basis function and probabilistic
neural networks are trained to recognize the waveform class.
According to the test result, the investigated technique can provide
satisfactory identification of the islanding condition in the
distribution system. |
format |
Article |
author |
Khamis, Aziah |
author_facet |
Khamis, Aziah |
author_sort |
Khamis, Aziah |
title |
An Effective Islanding Detection and
Classification Method Using Neuro-Phase
Space Technique |
title_short |
An Effective Islanding Detection and
Classification Method Using Neuro-Phase
Space Technique |
title_full |
An Effective Islanding Detection and
Classification Method Using Neuro-Phase
Space Technique |
title_fullStr |
An Effective Islanding Detection and
Classification Method Using Neuro-Phase
Space Technique |
title_full_unstemmed |
An Effective Islanding Detection and
Classification Method Using Neuro-Phase
Space Technique |
title_sort |
effective islanding detection and
classification method using neuro-phase
space technique |
publisher |
WASET |
publishDate |
2013 |
url |
http://eprints.utem.edu.my/id/eprint/9473/1/v78-208%28aziah_waset%29.pdf http://eprints.utem.edu.my/id/eprint/9473/ |
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