A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment
This paper addresses a new approach for predicting the generator rotor angle using an adaptive artificial neural network (AANN) for power system stability. The aim of this work is to predict the stability status for each generator when the system is under a contingency. This is based on the initial...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/28635/1/0000.pdf |
| _version_ | 1825947354960756736 |
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| author | Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Mariun, Norman |
| author_facet | Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Mariun, Norman |
| author_sort | Al-Masri, Ahmed Naufal A. |
| collection | UPM |
| description | This paper addresses a new approach for predicting the generator rotor angle using an adaptive artificial neural network (AANN) for power system stability. The aim of this work is to predict the stability status for each generator when the system is under a contingency. This is based on the initial condition of an operating point, which is represented by the generator rotor angle at a certain load level. An automatic data generation algorithm is developed for the training and testing process. The proposed method has been successfully tested on the IEEE 9-bus test system and the 87-bus system for Peninsular Malaysia. |
| first_indexed | 2024-03-06T08:12:06Z |
| format | Article |
| id | upm.eprints-28635 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T08:12:06Z |
| publishDate | 2013 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-286352016-06-06T07:22:05Z http://psasir.upm.edu.my/id/eprint/28635/ A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Mariun, Norman This paper addresses a new approach for predicting the generator rotor angle using an adaptive artificial neural network (AANN) for power system stability. The aim of this work is to predict the stability status for each generator when the system is under a contingency. This is based on the initial condition of an operating point, which is represented by the generator rotor angle at a certain load level. An automatic data generation algorithm is developed for the training and testing process. The proposed method has been successfully tested on the IEEE 9-bus test system and the 87-bus system for Peninsular Malaysia. IEEE 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/28635/1/0000.pdf Al-Masri, Ahmed Naufal A. and Ab Kadir, Mohd Zainal Abidin and Hizam, Hashim and Mariun, Norman (2013) A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment. IEEE Transactions on Power Systems, 28 (3). pp. 2516-2525. ISSN 0885-8950 10.1109/TPWRS.2013.2247069 |
| spellingShingle | Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Mariun, Norman A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment |
| title | A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment |
| title_full | A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment |
| title_fullStr | A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment |
| title_full_unstemmed | A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment |
| title_short | A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment |
| title_sort | novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment |
| url | http://psasir.upm.edu.my/id/eprint/28635/1/0000.pdf |
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