Artificial neural network approach to transmission line relaying
Thesis (M.Eng.)--Memorial University of Newfoundland, 1999. Engineering and Applied Science Bibliography: leaves 140-143 This thesis deals with the design of an Artificial Neural Network (ANN) based relay for transmission line protection. A novel feedforward neural network that indicates whether a f...
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ftmemorialunivdc:oai:collections.mun.ca:theses3/4171 2023-05-15T17:23:32+02:00 Artificial neural network approach to transmission line relaying Zahra, Fathima, 1971- Memorial University of Newfoundland. Faculty of Engineering and Applied Science 1998 xv, 145 leaves : ill. Image/jpeg; Application/pdf http://collections.mun.ca/cdm/ref/collection/theses3/id/4171 eng eng Electronic Theses and Dissertations (14.72 MB) -- http://collections.mun.ca/PDFs/theses/Zahra_Fathima.pdf a1358126 http://collections.mun.ca/cdm/ref/collection/theses3/id/4171 The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. Paper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries Neural networks (Computer science) Electric relays Protective relays Electric lines--Models Text Electronic thesis or dissertation 1998 ftmemorialunivdc 2015-08-06T19:17:37Z Thesis (M.Eng.)--Memorial University of Newfoundland, 1999. Engineering and Applied Science Bibliography: leaves 140-143 This thesis deals with the design of an Artificial Neural Network (ANN) based relay for transmission line protection. A novel feedforward neural network that indicates whether a fault is within or outside the protection zone (fault indication) of a transmission line is presented. This method has been extended to locate the distance of the fault (fault location). The proposed scheme utilizes the frequency components of the voltages and currents to make a decision. -- The first part of the work employed frequency components of one cycle of post- fault data as the inputs to the ANN. The results obtained were promising, thus forming the basis to improve the speed of the relaying decision. This is achieved by using the frequency components of half cycle of pre-fault and half-cycle post-fault data as the inputs to the ANN. -- The neural network employed is small in size, fast and robust. Data obtained from the Electromagnetic Transients Program (EMTP) for single-line-to-ground faults and three-phase faults have been used for testing and the results are found to be accurate. The performance of the trained neural network is good and the proposed ANN has the potential for implementation in a digital relay for transmission line protection. The results of the proposed ANN methodology are found to be accurate under the conditions of different fault location, fault inception angle and fault resistance. Thesis Newfoundland studies University of Newfoundland Memorial University of Newfoundland: Digital Archives Initiative (DAI) |
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Memorial University of Newfoundland: Digital Archives Initiative (DAI) |
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English |
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Neural networks (Computer science) Electric relays Protective relays Electric lines--Models |
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Neural networks (Computer science) Electric relays Protective relays Electric lines--Models Zahra, Fathima, 1971- Artificial neural network approach to transmission line relaying |
topic_facet |
Neural networks (Computer science) Electric relays Protective relays Electric lines--Models |
description |
Thesis (M.Eng.)--Memorial University of Newfoundland, 1999. Engineering and Applied Science Bibliography: leaves 140-143 This thesis deals with the design of an Artificial Neural Network (ANN) based relay for transmission line protection. A novel feedforward neural network that indicates whether a fault is within or outside the protection zone (fault indication) of a transmission line is presented. This method has been extended to locate the distance of the fault (fault location). The proposed scheme utilizes the frequency components of the voltages and currents to make a decision. -- The first part of the work employed frequency components of one cycle of post- fault data as the inputs to the ANN. The results obtained were promising, thus forming the basis to improve the speed of the relaying decision. This is achieved by using the frequency components of half cycle of pre-fault and half-cycle post-fault data as the inputs to the ANN. -- The neural network employed is small in size, fast and robust. Data obtained from the Electromagnetic Transients Program (EMTP) for single-line-to-ground faults and three-phase faults have been used for testing and the results are found to be accurate. The performance of the trained neural network is good and the proposed ANN has the potential for implementation in a digital relay for transmission line protection. The results of the proposed ANN methodology are found to be accurate under the conditions of different fault location, fault inception angle and fault resistance. |
author2 |
Memorial University of Newfoundland. Faculty of Engineering and Applied Science |
format |
Thesis |
author |
Zahra, Fathima, 1971- |
author_facet |
Zahra, Fathima, 1971- |
author_sort |
Zahra, Fathima, 1971- |
title |
Artificial neural network approach to transmission line relaying |
title_short |
Artificial neural network approach to transmission line relaying |
title_full |
Artificial neural network approach to transmission line relaying |
title_fullStr |
Artificial neural network approach to transmission line relaying |
title_full_unstemmed |
Artificial neural network approach to transmission line relaying |
title_sort |
artificial neural network approach to transmission line relaying |
publishDate |
1998 |
url |
http://collections.mun.ca/cdm/ref/collection/theses3/id/4171 |
genre |
Newfoundland studies University of Newfoundland |
genre_facet |
Newfoundland studies University of Newfoundland |
op_source |
Paper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries |
op_relation |
Electronic Theses and Dissertations (14.72 MB) -- http://collections.mun.ca/PDFs/theses/Zahra_Fathima.pdf a1358126 http://collections.mun.ca/cdm/ref/collection/theses3/id/4171 |
op_rights |
The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. |
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