Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review
High penetration of distributed generation resources (DGR) in distribution network provides many benefits in terms of high power quality, efficiency, and low carbon emissions in power system, However, efficient islanding detection and immediate disconnection of DGR is critical in order to avoid equi...
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my.um.eprints.158532019-09-05T07:38:05Z http://eprints.um.edu.my/15853/ Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review Raza, S. Mokhlis, Hazlie Arof, Hamzah Laghari, J.A. Wang, L. T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering High penetration of distributed generation resources (DGR) in distribution network provides many benefits in terms of high power quality, efficiency, and low carbon emissions in power system, However, efficient islanding detection and immediate disconnection of DGR is critical in order to avoid equipment damage, grid protection interference, and personnel safety hazards. Islanding detection techniques are mainly classified into remote, passive, active, and hybrid techniques. From these, passive techniques are more advantageous due to lower power quality degradation, lower cost, and widespread usage by power utilities. However, the main limitations of these techniques are that they possess a large non detection zones and require threshold setting. Various signal processing techniques and intelligent classifiers have been used to overcome the limitations of passive islanding. Signal processing techniques, in particular, are adopted due to their versatility, stability, cost effectiveness, and ease of modification. This paper presents a comprehensive overview of signal processing techniques used to improve common passive islanding detection techniques. A performance comparison between the signal processing based islanding detection techniques with existing techniques are also provided. Finally, this paper outlines the relative advantages and limitations of the signal processing techniques in order to provide basic guidelines for researchers and field engineers in determining the best method for their system. (C) 2015 Elsevier Ltd. All rights reserved. Elsevier 2015-05-15 Article PeerReviewed application/pdf en http://eprints.um.edu.my/15853/1/Application_of_signal_processing_techniques_for_islanding_detection_of_distributed_generation.pdf Raza, S. and Mokhlis, Hazlie and Arof, Hamzah and Laghari, J.A. and Wang, L. (2015) Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review. Energy Conversion and Management, 96. pp. 613-624. ISSN 0196-8904 http://www.sciencedirect.com/science/article/pii/S0196890415002393 10.1016/j.enconman.2015.03.029 |
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T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Raza, S. Mokhlis, Hazlie Arof, Hamzah Laghari, J.A. Wang, L. Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review |
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High penetration of distributed generation resources (DGR) in distribution network provides many benefits in terms of high power quality, efficiency, and low carbon emissions in power system, However, efficient islanding detection and immediate disconnection of DGR is critical in order to avoid equipment damage, grid protection interference, and personnel safety hazards. Islanding detection techniques are mainly classified into remote, passive, active, and hybrid techniques. From these, passive techniques are more advantageous due to lower power quality degradation, lower cost, and widespread usage by power utilities. However, the main limitations of these techniques are that they possess a large non detection zones and require threshold setting. Various signal processing techniques and intelligent classifiers have been used to overcome the limitations of passive islanding. Signal processing techniques, in particular, are adopted due to their versatility, stability, cost effectiveness, and ease of modification. This paper presents a comprehensive overview of signal processing techniques used to improve common passive islanding detection techniques. A performance comparison between the signal processing based islanding detection techniques with existing techniques are also provided. Finally, this paper outlines the relative advantages and limitations of the signal processing techniques in order to provide basic guidelines for researchers and field engineers in determining the best method for their system. (C) 2015 Elsevier Ltd. All rights reserved. |
format |
Article |
author |
Raza, S. Mokhlis, Hazlie Arof, Hamzah Laghari, J.A. Wang, L. |
author_facet |
Raza, S. Mokhlis, Hazlie Arof, Hamzah Laghari, J.A. Wang, L. |
author_sort |
Raza, S. |
title |
Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review |
title_short |
Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review |
title_full |
Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review |
title_fullStr |
Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review |
title_full_unstemmed |
Application of signal processing techniques for islanding detection of distributed generation in distribution network : A review |
title_sort |
application of signal processing techniques for islanding detection of distributed generation in distribution network : a review |
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Elsevier |
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2015 |
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http://eprints.um.edu.my/15853/1/Application_of_signal_processing_techniques_for_islanding_detection_of_distributed_generation.pdf http://eprints.um.edu.my/15853/ http://www.sciencedirect.com/science/article/pii/S0196890415002393 |
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13.211869 |