Fault localization method for power distribution systems based on gated graph neural networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-021-01223-7.pdf
Reference20 articles.
1. Aslan Y (2012) An alternative approach to fault location on power distribution feeders with embedded remote-end power generation using artificial neural networks. Electr Eng. https://doi.org/10.1007/s00202-011-0218-2
2. Cho K, van Merrienboer B, Gulcehre C, Bahdanau D, Bougares F, Schwenk H, Bengio Y (2014) Learning phrase representations using rnn encoder-decoder for statistical machine translation. arXiv:1406.1078
3. Das R, Madani V, Aminifar F, McDonald J, Venkata SS, Novosel D, Bose A, Shahidehpour M (2015) Distribution automation strategies: evolution of technologies and the business case. IEEE Trans Smart Grid 6(4):2166–2175. https://doi.org/10.1109/TSG.2014.2368393
4. Dashtdar M (2018) Fault location in distribution network based on fault current analysis using artificial neural. Network 1:18–32
5. Dehghani F, Nezami H (2013) A new fault location technique on radial distribution systems using artificial neural network. In: 22nd international conference and exhibition on electricity distribution (CIRED 2013), pp 1–4. https://doi.org/10.1049/cp.2013.0697
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