ANN application techniques for power system stability estimation
The implementation of artificial neural networks (ANN) as a power system stability monitoring tool is a viable option, introducing dynamic and intelligent solution to utility operators. This paper examines the performance of two nonlinear multilayer ANN models which are similar in structural topolog...
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| Format: | Article |
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Taylor & Francis
2000
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| author | Moghavvemi, Mahmoud Yang, S.S. |
| author_facet | Moghavvemi, Mahmoud Yang, S.S. |
| author_sort | Moghavvemi, Mahmoud |
| collection | UM |
| description | The implementation of artificial neural networks (ANN) as a power system stability monitoring tool is a viable option, introducing dynamic and intelligent solution to utility operators. This paper examines the performance of two nonlinear multilayer ANN models which are similar in structural topology and training emphasis but different by way of the utilization of their net or basis function. The performance of both models were compared for the estimation of stability index to gauge the stability of a power system network. Although tests were conducted in a simulated environment, loading patterns analyzed in this case study were realistically generated, and hence test results realistically accentuates the potential of ANN for practical on-line dynamic system implementation. © 2000, Taylor & Francis Group, LLC. All rights reserved. |
| first_indexed | 2024-03-06T05:24:29Z |
| format | Article |
| id | um.eprints-9691 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:24:29Z |
| publishDate | 2000 |
| publisher | Taylor & Francis |
| record_format | dspace |
| spelling | um.eprints-96912021-10-20T01:15:14Z http://eprints.um.edu.my/9691/ ANN application techniques for power system stability estimation Moghavvemi, Mahmoud Yang, S.S. TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering The implementation of artificial neural networks (ANN) as a power system stability monitoring tool is a viable option, introducing dynamic and intelligent solution to utility operators. This paper examines the performance of two nonlinear multilayer ANN models which are similar in structural topology and training emphasis but different by way of the utilization of their net or basis function. The performance of both models were compared for the estimation of stability index to gauge the stability of a power system network. Although tests were conducted in a simulated environment, loading patterns analyzed in this case study were realistically generated, and hence test results realistically accentuates the potential of ANN for practical on-line dynamic system implementation. © 2000, Taylor & Francis Group, LLC. All rights reserved. Taylor & Francis 2000 Article PeerReviewed Moghavvemi, Mahmoud and Yang, S.S. (2000) ANN application techniques for power system stability estimation. Electric Machines & Power Systems, 28 (2). pp. 167-178. ISSN 0731-356X, DOI https://doi.org/10.1080/073135600268441 <https://doi.org/10.1080/073135600268441>. https://doi.org/10.1080/073135600268441 doi:10.1080/073135600268441 |
| spellingShingle | TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Moghavvemi, Mahmoud Yang, S.S. ANN application techniques for power system stability estimation |
| title | ANN application techniques for power system stability estimation |
| title_full | ANN application techniques for power system stability estimation |
| title_fullStr | ANN application techniques for power system stability estimation |
| title_full_unstemmed | ANN application techniques for power system stability estimation |
| title_short | ANN application techniques for power system stability estimation |
| title_sort | ann application techniques for power system stability estimation |
| topic | TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering |
| work_keys_str_mv | AT moghavvemimahmoud annapplicationtechniquesforpowersystemstabilityestimation AT yangss annapplicationtechniquesforpowersystemstabilityestimation |