A novel islanding detection technique using modified Slantlet transform in multi-distributed generation
In this paper, a new hybrid islanding detection scheme based on a combination of a modified Slantlet Transform (MSLT) and machine learning is applied to a passive time frequency islanding detection of multiple distributed generation units. A Harmony Search Algorithm (HSA) is used to optimally specif...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/80440/ http://psasir.upm.edu.my/id/eprint/80440/1/SLANTET.pdf |
| _version_ | 1848858905192431616 |
|---|---|
| author | Hizam, Hashim Ahmadipour, Masoud Mohd Radzi, Mohd Amran Othman, Mohammad Lutfi Chireh, Nikta |
| author_facet | Hizam, Hashim Ahmadipour, Masoud Mohd Radzi, Mohd Amran Othman, Mohammad Lutfi Chireh, Nikta |
| author_sort | Hizam, Hashim |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In this paper, a new hybrid islanding detection scheme based on a combination of a modified Slantlet Transform (MSLT) and machine learning is applied to a passive time frequency islanding detection of multiple distributed generation units. A Harmony Search Algorithm (HSA) is used to optimally specify suitable scales of Slantlet transform and Slantlet decomposition levels for accurate islanding classification. Slantlet transform is utilized to derive the features in the required detection parameters measured from islanding and non-islanding events using identified Slantlet scales. In order to automate classification process, machine learning classifiers are utilized to detect islanding and non-islanding conditions with an objective of increasing the detection rate and avoiding nuisance distributed generation tripping during non-islanding situations. Islanding and non-islanding events are simulated for a multi-distributed generations system and used to assess the performance of the proposed anti-islanding protection method. The numerical results showing the efficiency of the proposed islanding detection technique are explained and conclusions are drawn. |
| first_indexed | 2025-11-15T12:20:52Z |
| format | Article |
| id | upm-80440 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:20:52Z |
| publishDate | 2019 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-804402020-11-09T15:19:29Z http://psasir.upm.edu.my/id/eprint/80440/ A novel islanding detection technique using modified Slantlet transform in multi-distributed generation Hizam, Hashim Ahmadipour, Masoud Mohd Radzi, Mohd Amran Othman, Mohammad Lutfi Chireh, Nikta In this paper, a new hybrid islanding detection scheme based on a combination of a modified Slantlet Transform (MSLT) and machine learning is applied to a passive time frequency islanding detection of multiple distributed generation units. A Harmony Search Algorithm (HSA) is used to optimally specify suitable scales of Slantlet transform and Slantlet decomposition levels for accurate islanding classification. Slantlet transform is utilized to derive the features in the required detection parameters measured from islanding and non-islanding events using identified Slantlet scales. In order to automate classification process, machine learning classifiers are utilized to detect islanding and non-islanding conditions with an objective of increasing the detection rate and avoiding nuisance distributed generation tripping during non-islanding situations. Islanding and non-islanding events are simulated for a multi-distributed generations system and used to assess the performance of the proposed anti-islanding protection method. The numerical results showing the efficiency of the proposed islanding detection technique are explained and conclusions are drawn. Elsevier 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/80440/1/SLANTET.pdf Hizam, Hashim and Ahmadipour, Masoud and Mohd Radzi, Mohd Amran and Othman, Mohammad Lutfi and Chireh, Nikta (2019) A novel islanding detection technique using modified Slantlet transform in multi-distributed generation. International Journal of Electrical Power and Energy Systems, 112. pp. 460-475. ISSN 0142-0615 https://www.sciencedirect.com/science/article/pii/S0142061519300985 10.1016/j.ijepes.2019.05.008 |
| spellingShingle | Hizam, Hashim Ahmadipour, Masoud Mohd Radzi, Mohd Amran Othman, Mohammad Lutfi Chireh, Nikta A novel islanding detection technique using modified Slantlet transform in multi-distributed generation |
| title | A novel islanding detection technique using modified Slantlet transform in multi-distributed generation |
| title_full | A novel islanding detection technique using modified Slantlet transform in multi-distributed generation |
| title_fullStr | A novel islanding detection technique using modified Slantlet transform in multi-distributed generation |
| title_full_unstemmed | A novel islanding detection technique using modified Slantlet transform in multi-distributed generation |
| title_short | A novel islanding detection technique using modified Slantlet transform in multi-distributed generation |
| title_sort | novel islanding detection technique using modified slantlet transform in multi-distributed generation |
| url | http://psasir.upm.edu.my/id/eprint/80440/ http://psasir.upm.edu.my/id/eprint/80440/ http://psasir.upm.edu.my/id/eprint/80440/ http://psasir.upm.edu.my/id/eprint/80440/1/SLANTET.pdf |