Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali
This thesis presents the development of an Artificial Neural Network (ANN) based technique for reactive power dispatch that aims to improve voltage stability of a power system. In this study, a multi-layer feed forward ANN with error back propagation algorithm was used. The proposed method was teste...
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
1995
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| الوصول للمادة أونلاين: | https://ir.uitm.edu.my/id/eprint/68745/1/68745.pdf |
| الوسوم: |
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my-uitm-ir.687452024-10-03T07:25:02Z Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali 1995 Norjali, Rasida Neural networks (Computer science) Dynamoelectric machinery and auxiliaries.Including generators, motors, transformers This thesis presents the development of an Artificial Neural Network (ANN) based technique for reactive power dispatch that aims to improve voltage stability of a power system. In this study, a multi-layer feed forward ANN with error back propagation algorithm was used. The proposed method was tested on two models, which are the 6 bus, and IEEE 14 bus interconnected systems. The testing and training data were generated by Fast Decoupled Load Flow method and the voltage stability at a load bus was measured by evaluating the voltage stability index, i.e. L-factor, developed in reference [1]. The results show that the ANN could be used to determine the value of reactive power and to predict voltage stability level for power system, since they are in close agreement with the calculating results. 1995 Thesis https://ir.uitm.edu.my/id/eprint/68745/ https://ir.uitm.edu.my/id/eprint/68745/1/68745.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Abdul Rahman, Titik Khawa |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| advisor |
Abdul Rahman, Titik Khawa |
| topic |
Neural networks (Computer science) Neural networks (Computer science) |
| spellingShingle |
Neural networks (Computer science) Neural networks (Computer science) Norjali, Rasida Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali |
| description |
This thesis presents the development of an Artificial Neural Network (ANN) based technique for reactive power dispatch that aims to improve voltage stability of a power system. In this study, a multi-layer feed forward ANN with error back propagation algorithm was used. The proposed method was tested on two models, which are the 6 bus, and IEEE 14 bus interconnected systems. The testing and training data were generated by Fast Decoupled Load Flow method and the voltage stability at a load bus was measured by evaluating the voltage stability index, i.e. L-factor, developed in reference [1]. The results show that the ANN could be used to determine the value of reactive power and to predict voltage stability level for power system, since they are in close agreement with the calculating results. |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Norjali, Rasida |
| author_facet |
Norjali, Rasida |
| author_sort |
Norjali, Rasida |
| title |
Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali |
| title_short |
Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali |
| title_full |
Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali |
| title_fullStr |
Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali |
| title_full_unstemmed |
Reactive power dispatch incooperating voltage stability improvement using artificial neural network / Rasida Norjali |
| title_sort |
reactive power dispatch incooperating voltage stability improvement using artificial neural network / rasida norjali |
| granting_institution |
Universiti Teknologi MARA (UiTM) |
| granting_department |
Faculty of Electrical Engineering |
| publishDate |
1995 |
| url |
https://ir.uitm.edu.my/id/eprint/68745/1/68745.pdf |
| _version_ |
1818587919462432768 |