Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed
Recently research has shown that ANN is promising solution to many applications especially for non-linear problem in power system, which is difficult for conventional technique. The potential of application of ANN as an alternative approach for solving certain difficult power system problem where co...
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2004
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my.uitm.ir.848262024-01-16T18:08:08Z https://ir.uitm.edu.my/id/eprint/84826/ Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed Mohamed, Sabrita Recently research has shown that ANN is promising solution to many applications especially for non-linear problem in power system, which is difficult for conventional technique. The potential of application of ANN as an alternative approach for solving certain difficult power system problem where conventional methods have not achieved desired speed couldn't be understand. This report presents an application of Artificial Neural Network for determining compensating capacitor location, sizing and power loss minimum in power system. This training data was obtain from calculated capacitor location, sizing and power loss with Newton-Raphson method using Borland C++ program and apply to the artificial neural network using Back-propagation method in the MATLAB. The proposed technique was tested on 6 bus system. The result shows that the proposed ANN technique is highly accurate and capable predict at faster rate. 2004 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/84826/1/84826.pdf Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed. (2004) Degree thesis, thesis, Universiti Teknologi MARA (UiTM). |
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Recently research has shown that ANN is promising solution to many applications especially for non-linear problem in power system, which is difficult for conventional technique. The potential of application of ANN as an alternative approach for solving certain difficult power system problem where conventional methods have not achieved desired speed couldn't be understand. This report presents an application of Artificial Neural Network for determining compensating capacitor location, sizing and power loss minimum in power system. This training data was obtain from calculated capacitor location, sizing and power loss with Newton-Raphson method using Borland C++ program and apply to the artificial neural network using Back-propagation method in the MATLAB. The proposed technique was tested on 6 bus system. The result shows that the proposed ANN technique is highly accurate and capable predict at faster rate. |
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Mohamed, Sabrita |
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Mohamed, Sabrita Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed |
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Mohamed, Sabrita |
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Mohamed, Sabrita |
title |
Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed |
title_short |
Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed |
title_full |
Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed |
title_fullStr |
Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed |
title_full_unstemmed |
Application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / Sabrita Mohamed |
title_sort |
application of artificial neural network for determining compensating capacitor location, sizing loss minimization in a power system / sabrita mohamed |
publishDate |
2004 |
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https://ir.uitm.edu.my/id/eprint/84826/1/84826.pdf https://ir.uitm.edu.my/id/eprint/84826/ |
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