Identification the Faulty Components in Power Networks Based on Wide Area Information and RBF Neural Network

Yu Fang; Zheng Wei Chang; Hao Wu; Xian Feng Tang

doi:10.4028/www.scientific.net/AMM.568-570.842

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 568-570Identification the Faulty Components in Power...

Identification the Faulty Components in Power Networks Based on Wide Area Information and RBF Neural Network

Abstract:

Using the wide area information of the IED, the identification faulty components network is constructed based on RBF neural network. Using the state information collected by line IED as the input vector, training samples matrix of identification faulty components network is established to train RBF neural network of faulty components identification, and to test the recognition network using the sample matrix under random failure, and then the faulty line IED can be identified, the faulty components can be determined. Experiments show that the new algorithm based on RBF has higher accuracy rate and better fault-tolerant.

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Periodical:

Applied Mechanics and Materials (Volumes 568-570)

Pages:

842-847

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.568-570.842

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Online since:

June 2014

Authors:

Yu Fang, Zheng Wei Chang, Hao Wu*, Xian Feng Tang

Keywords:

Identification the Faulty Components, Line IED, Power Grid, RBF

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* - Corresponding Author

References

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