An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique

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)

[img]
Preview
PDF
v78-208(aziah_waset).pdf - Published Version

Download (991kB)

Abstract

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.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Electrical Engineering > Department of Industrial Power
Depositing User: MRS Aziah Khamis
Date Deposited: 05 Sep 2013 01:56
Last Modified: 28 May 2015 04:04
URI: http://eprints.utem.edu.my/id/eprint/9473
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item