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Fault detection and classification in three phase series compensated transmission line using ANN

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cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtualsource.department 1b3bdf0a-83ae-467d-bdef-d27e90595670
cris.virtualsource.department 7b496cc1-3619-403b-afea-d7965df6a332
cris.virtualsource.department 90adfd5f-f0d7-495a-a6ca-51d39de9f728
cris.virtualsource.department 64a6c5a1-2e6d-4739-b838-ade8f975c6ac
cris.virtualsource.department 7d1ed5ce-c97b-4775-b51c-ce3dcc32f6b9
cris.virtualsource.department 5030ad05-3cf2-44ab-9615-9d635d296d06
dc.contributor.author Norfadilah Rosle
dc.contributor.author Noor Fazliana Fadzail
dc.contributor.author M I A Halim
dc.contributor.author Mohamad Nur Khairul Hafizi Rohani
dc.contributor.author Muhammad Izuan Fahmi Romli
dc.contributor.author Leow Wai Zhe
dc.contributor.author Nur Najihah Abu Bakar
dc.date.accessioned 2025-11-10T02:10:19Z
dc.date.available 2025-11-10T02:10:19Z
dc.date.issued 2020
dc.description.abstract Series compensation consists of capacitors in series is used in the transmission lines as a tool to improve the performance after disturbed by a fault. Transmission line needs a protection scheme to protect the lines from faults due to natural disturbances, short circuit and open circuit faults. The fault can happen in any location of transmission line and it is important to know which location has been affected. So that, the fault can be eliminated and can maintain the optimum performance. Therefore, in this paper Artificial Neural Network (ANN) is used to detect and classified the fault happen in single line to ground fault and three phase to ground fault. Two different tests of each types of fault have been tested in order to prove the effectiveness of ANN to detect the fault location by using different length and fault resistance. The simulation has been accomplished in MATLAB with ANN fitting tool which build and train the network before evaluated its performance using regression analysis. The analysis shows that the ANN can accurately detect the different types of faults and classified it into the respective category even the random vectors are put on the system are used.
dc.identifier.doi 10.1088/1742-6596/1432/1/012013
dc.identifier.uri https://iopscience.iop.org/article/10.1088/1742-6596/1432/1/012013/pdf
dc.identifier.uri https://iopscience.iop.org/article/10.1088/1742-6596/1432/1/012013
dc.identifier.uri https://hdl.handle.net/20.500.14170/14999
dc.language.iso en
dc.publisher IOP Publishing
dc.relation.conference 1st International Conference on Emerging Electrical Energy, Electronics and Computing Technologies 2019, Melaka, Malaysia
dc.relation.ispartof Journal of Physics
dc.relation.ispartofseries Conference Series
dc.relation.issn 1742-6588
dc.relation.issn 1742-6596
dc.title Fault detection and classification in three phase series compensated transmission line using ANN
dc.type Resource Types::text::conference output::conference proceedings
dspace.entity.type Publication
oaire.citation.endPage 8
oaire.citation.issue 1
oaire.citation.startPage 1
oaire.citation.volume 1432
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Respack Poly Film Sdn Bhd, Kedah
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
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