Abstract
This paper presents a neuro-fuzzy approach to power quality assessment. Electrical equipment susceptibility to disturbances varies from type to type. Additionally, not only one physical phenomenon (e.g. harmonics) can cause equipment malfunctioning or damage, but more likely a superposition of some different disturbances. The authors propose an automated neuro-fuzzy approach to power quality indicia bundling which is correlated to equipment susceptibility. Whereby distortion power is seen as one of the power quality indices. The neuro-fuzzy analyzer matches logically different indices and gives as output one value describing the possible thread to electrical equipment. A reduction of data amount to be analysed by a system engineer is aimed.
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