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A neural network based fault detector for power distribution systems

  • Part VII: Prediction, Forecasting, and Monitoring
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Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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Abstract

This paper presents a fault detector for power distribution systems based on the use of feedforward neural networks. The described method is successfully tested through several simulations. The efficiency of the algorithm to recognize faulty feeders without measuring any voltage in the network and without any threshold is emphasized. Moreover, the sampling frequency of signals and the errors that measuring instruments may introduce do not interfere with the right functionning of the detector.

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References

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Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Assef, Y., Bastard, P., Meunier, M. (1997). A neural network based fault detector for power distribution systems. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020301

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  • DOI: https://doi.org/10.1007/BFb0020301

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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