Comparison between the performance of ANN-based loss of mains relays using multi-layer and non-layered perceptron approaches
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Loss of mains is a condition whereby an embedded/distributed generator becomes islanded with part of a public load. This is usually caused by disturbances on the associated utility network which results in having an EG (embedded generation) to become “islanded” with a public load. This condition is highly undesirable and should be correctly detected in order to ensure the tripping of the generator affected by such conditions. Currently the two methods most commonly in use to detect LOM (loss of mains) utilise ROCOF (rate of change of frequency) and PDM (vector surge) techniques, either on their own, or in tandem. However, these methods have not proved to be totally reliable. This paper reports the development of a new relay for detecting LOM. It is based on the application of artificial neural network (ANN). Two ANN architectures have been considered; one based on multi-layer perceptron approach while the other based on a non-layered approach using NeuralWorks Predict features.