Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems
This article proposes a novel fault-localization method that is based on the nonintrusive fault-monitoring (NIFM) techniques in high-voltage/extra-high-voltage (HV/EHV) power transmission networks. In this work, the fault signals measured at the utilities are extracted by the hyperbolic S-transform...
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2021
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| الوصول للمادة أونلاين: | http://irep.iium.edu.my/88312/7/88312_Fault%20Location%20Identification.pdf http://irep.iium.edu.my/88312/ https://ieeexplore.ieee.org/document/9285331 |
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my.iium.irep.883122021-02-10T04:54:40Z http://irep.iium.edu.my/88312/ Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems Chang, Hsueh-Hsien Yang, Chuan Choong Lee, Wei-Jen TK3001 Distribution or transmission of electric power. The electric power circuit TK4001 Applications of electric power TK452 Electric apparatus and materials. Electric circuits. Electric networks This article proposes a novel fault-localization method that is based on the nonintrusive fault-monitoring (NIFM) techniques in high-voltage/extra-high-voltage (HV/EHV) power transmission networks. In this work, the fault signals measured at the utilities are extracted by the hyperbolic S-transform (HST) before going through the identification process. To carefully select coefficients of the HST representing fault transient signals and reduce the size of inputs for recognition algorithms, power-spectrum-based HST is adopted in this article to quantitatively transform the HST coefficients (HSTCs). After the processes of feature selection, the fault-location indicator is recognized by the support vector machines (SVMs). To examine and validate the proposed methodology, various fault types in a sample power system are simulated by using the electromagnetic transient program (EMTP). The simulation results reveal that the proposed methods demonstrate a high success rate of fault-location identification in power transmission networks for NIFM applications. IEEE 2021-03 Article PeerReviewed application/pdf en http://irep.iium.edu.my/88312/7/88312_Fault%20Location%20Identification.pdf Chang, Hsueh-Hsien and Yang, Chuan Choong and Lee, Wei-Jen (2021) Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems. IEEE Industry Applications Magazine, 27 (2). pp. 76-89. ISSN 2158-4893 E-ISSN 2158-4907 https://ieeexplore.ieee.org/document/9285331 10.1109/MIAS.2020.3024493 |
| institution |
Universiti Islam Antarabangsa Malaysia |
| building |
IIUM Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
International Islamic University Malaysia |
| content_source |
IIUM Repository (IREP) |
| url_provider |
http://irep.iium.edu.my/ |
| language |
English |
| topic |
TK3001 Distribution or transmission of electric power. The electric power circuit TK4001 Applications of electric power TK452 Electric apparatus and materials. Electric circuits. Electric networks |
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TK3001 Distribution or transmission of electric power. The electric power circuit TK4001 Applications of electric power TK452 Electric apparatus and materials. Electric circuits. Electric networks Chang, Hsueh-Hsien Yang, Chuan Choong Lee, Wei-Jen Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems |
| description |
This article proposes a novel fault-localization method that is based on the nonintrusive fault-monitoring (NIFM) techniques in high-voltage/extra-high-voltage (HV/EHV) power transmission networks. In this work, the fault signals measured at the utilities are extracted by the hyperbolic S-transform (HST) before going through the identification process. To carefully select coefficients of the HST representing fault transient signals and reduce the size of inputs for recognition algorithms, power-spectrum-based HST is adopted in this article to quantitatively transform the HST coefficients (HSTCs). After the processes of feature selection, the fault-location indicator is recognized by the support vector machines (SVMs). To examine and validate the proposed methodology, various fault types in a sample power system are simulated by using the electromagnetic transient program (EMTP). The simulation results reveal that the proposed methods demonstrate a high success rate of fault-location identification in power transmission networks for NIFM applications. |
| format |
Article |
| author |
Chang, Hsueh-Hsien Yang, Chuan Choong Lee, Wei-Jen |
| author_facet |
Chang, Hsueh-Hsien Yang, Chuan Choong Lee, Wei-Jen |
| author_sort |
Chang, Hsueh-Hsien |
| title |
Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems |
| title_short |
Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems |
| title_full |
Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems |
| title_fullStr |
Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems |
| title_full_unstemmed |
Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems |
| title_sort |
fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems |
| publisher |
IEEE |
| publishDate |
2021 |
| url |
http://irep.iium.edu.my/88312/7/88312_Fault%20Location%20Identification.pdf http://irep.iium.edu.my/88312/ https://ieeexplore.ieee.org/document/9285331 |
| _version_ |
1691732937409560576 |
| score |
13.251813 |