Risk-based voltage collapse assessment using generalized regression neural network
This paper describes the implementation of a fast and accurate intelligent technique using generalized regression neural network to assess the risk of voltage collapse in power systems. The risk of voltage collapse is defined as the product of the probability of transmission line outage and its seve...
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my.uniten.dspace-305252023-12-29T15:48:55Z Risk-based voltage collapse assessment using generalized regression neural network Marsadek M. Mohamed A. Nopiah Z.M. 26423183000 57195440511 24503340900 generalised regression neural network probability Risk severity voltage collapse Electric lines Electrical engineering Information science Outages Power transmission Probability Rating Regression analysis Risk assessment Transmission line theory Assessment methods Failure rate Function models Generalized regression neural networks Intelligent techniques Real power systems Regression neural networks Risk-based severity Transmission line voltage collapse Weather conditions Neural networks This paper describes the implementation of a fast and accurate intelligent technique using generalized regression neural network to assess the risk of voltage collapse in power systems. The risk of voltage collapse is defined as the product of the probability of transmission line outage and its severity associated with voltage collapse. The effect of weather in the probability of transmission line outage is taken into account in which the failure rate of each transmission line with respect to weather conditions is calculated. A new severity function model that utilises the voltage collapse prediction index is also considered in this assessment method. The performance of the generalised regression neural network is evaluated using mean absolute and mean square errors. The proposed risk based voltage collapse assessment method has been validated on a real power system. � 2011 IEEE. Final 2023-12-29T07:48:55Z 2023-12-29T07:48:55Z 2011 Conference paper 10.1109/ICEEI.2011.6021767 2-s2.0-80054027939 https://www.scopus.com/inward/record.uri?eid=2-s2.0-80054027939&doi=10.1109%2fICEEI.2011.6021767&partnerID=40&md5=051d13d217ea6609b72d90471a9a5896 https://irepository.uniten.edu.my/handle/123456789/30525 6021767 Scopus |
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generalised regression neural network probability Risk severity voltage collapse Electric lines Electrical engineering Information science Outages Power transmission Probability Rating Regression analysis Risk assessment Transmission line theory Assessment methods Failure rate Function models Generalized regression neural networks Intelligent techniques Real power systems Regression neural networks Risk-based severity Transmission line voltage collapse Weather conditions Neural networks |
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generalised regression neural network probability Risk severity voltage collapse Electric lines Electrical engineering Information science Outages Power transmission Probability Rating Regression analysis Risk assessment Transmission line theory Assessment methods Failure rate Function models Generalized regression neural networks Intelligent techniques Real power systems Regression neural networks Risk-based severity Transmission line voltage collapse Weather conditions Neural networks Marsadek M. Mohamed A. Nopiah Z.M. Risk-based voltage collapse assessment using generalized regression neural network |
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This paper describes the implementation of a fast and accurate intelligent technique using generalized regression neural network to assess the risk of voltage collapse in power systems. The risk of voltage collapse is defined as the product of the probability of transmission line outage and its severity associated with voltage collapse. The effect of weather in the probability of transmission line outage is taken into account in which the failure rate of each transmission line with respect to weather conditions is calculated. A new severity function model that utilises the voltage collapse prediction index is also considered in this assessment method. The performance of the generalised regression neural network is evaluated using mean absolute and mean square errors. The proposed risk based voltage collapse assessment method has been validated on a real power system. � 2011 IEEE. |
| author2 |
26423183000 |
| author_facet |
26423183000 Marsadek M. Mohamed A. Nopiah Z.M. |
| format |
Conference paper |
| author |
Marsadek M. Mohamed A. Nopiah Z.M. |
| author_sort |
Marsadek M. |
| title |
Risk-based voltage collapse assessment using generalized regression neural network |
| title_short |
Risk-based voltage collapse assessment using generalized regression neural network |
| title_full |
Risk-based voltage collapse assessment using generalized regression neural network |
| title_fullStr |
Risk-based voltage collapse assessment using generalized regression neural network |
| title_full_unstemmed |
Risk-based voltage collapse assessment using generalized regression neural network |
| title_sort |
risk-based voltage collapse assessment using generalized regression neural network |
| publishDate |
2023 |
| _version_ |
1806426218351820800 |
| score |
13.211869 |