Advances in Electrical and Electronic Engineering (Jan 2018)

A Neural Network Based Response Model for High Voltage Circuit-Breaker Testing

  • Wesley Doorsamy,
  • Pitshou Bokoro

DOI
https://doi.org/10.15598/aeee.v16i3.2845
Journal volume & issue
Vol. 16, no. 3
pp. 311 – 317

Abstract

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Innovative test methods for circuit breakers are constantly sought after to reduce maintenance time and costs, yet still provide accurate assessment of this critical substation equipment. This paper proposes a novel method for response modelling of high voltage SF6 circuit breakers, based on artificial neural networks, to provide a means of assessing its condition. The proposed method enables a timing response model of the circuit breaker to be developed using trip command parameters. In this paper, an experimental setup is used to perform trip response testing of a three-phase 75 kV circuit breaker. The obtained data is then used to train, validate and test a Bayesian regularised artificial neural network that can predict response times of the breaker for a given set of trip command parameters.

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