Analysis of Influence of Power Quality Disturbances using a Neuro-Fuzzy System

P. Janik, Z. Leonowicz, T. Lobos, and Z. Waclawek (Poland)


Neural Networks, Fuzzy Logic, Power Quality


The authors propose an automated neuro-fuzzy system approach (with neural network subsystem) to power quality assessment incorporating equipment susceptibility patterns. The system is expected to handle dependencies between superposition of different disturbances and specific devices’ susceptibility to disturbances. Two neural network architectures were applied: a well known radial-basis neural networks for automatic rules’ generation and a neuro-fuzzy system for overlaid disturbances influence modeling. Proposed approach can help to predict damages or abnormal functioning of devices and implement adequate countermeasures.

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