ANN-based technique for transient stability / Norazlin Ahmad
Transient stability prediction (TSP) in a power system network is not feasible due to intensive computation involvement. Artificial neural network (ANN) has been proposed as one of the approaches to this problem based on its ability to quickly map nonlinear relationships between the input and the ou...
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2007
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| Online Access: | https://ir.uitm.edu.my/id/eprint/84640/1/84640.pdf |
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my-uitm-ir.846402024-01-29T04:11:03Z ANN-based technique for transient stability / Norazlin Ahmad 2007 Ahmad, Norazlin Transient stability prediction (TSP) in a power system network is not feasible due to intensive computation involvement. Artificial neural network (ANN) has been proposed as one of the approaches to this problem based on its ability to quickly map nonlinear relationships between the input and the output data. In this stage, input variables and targeted output will be identified. Consequently, training and testing program codes will be developed in MATLAB in order to implement the artificial neural network prediction process. Eventually, a fully- trained artificial neural network should be successfully developed which should be able to perform the TSP without having to conduct the conventional transient stability analysis. In order to realize the effectiveness of the proposed technique, a standard test system was utilized for validation purpose. 2007 Thesis https://ir.uitm.edu.my/id/eprint/84640/ https://ir.uitm.edu.my/id/eprint/84640/1/84640.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Musirin, Ismail |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| advisor |
Musirin, Ismail |
| description |
Transient stability prediction (TSP) in a power system network is not feasible due to intensive computation involvement. Artificial neural network (ANN) has been proposed as one of the approaches to this problem based on its ability to quickly map nonlinear relationships between the input and the output data. In this stage, input variables and targeted output will be identified. Consequently, training and testing program codes will be developed in MATLAB in order to implement the artificial neural network prediction process. Eventually, a fully- trained artificial neural network should be successfully developed which should be able to perform the TSP without having to conduct the conventional transient stability analysis. In order to realize the effectiveness of the proposed technique, a standard test system was utilized for validation purpose. |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Ahmad, Norazlin |
| spellingShingle |
Ahmad, Norazlin ANN-based technique for transient stability / Norazlin Ahmad |
| author_facet |
Ahmad, Norazlin |
| author_sort |
Ahmad, Norazlin |
| title |
ANN-based technique for transient stability / Norazlin Ahmad |
| title_short |
ANN-based technique for transient stability / Norazlin Ahmad |
| title_full |
ANN-based technique for transient stability / Norazlin Ahmad |
| title_fullStr |
ANN-based technique for transient stability / Norazlin Ahmad |
| title_full_unstemmed |
ANN-based technique for transient stability / Norazlin Ahmad |
| title_sort |
ann-based technique for transient stability / norazlin ahmad |
| granting_institution |
Universiti Teknologi MARA (UiTM) |
| granting_department |
Faculty of Electrical Engineering |
| publishDate |
2007 |
| url |
https://ir.uitm.edu.my/id/eprint/84640/1/84640.pdf |
| _version_ |
1794192033857929216 |