A cascade-type hierarchical fuzzy system with additional defuzzification of layers for the automatic power quality diagnosis
2019
Abstract In general the power quality diagnosis of low-voltage electrical systems is a difficult issue due to the nuances of different power quality standards around the world and the uncertainties characteristics of the evaluation parameters. In this framework, this paper proposes a new methodology for diagnosing the power quality by means of a cascade-type hierarchical fuzzy system with additional defuzzification of layers (C-HFS-ADL), also proposed in this paper, which is able to evaluate the power quality indices in steady-state (total harmonic distortions, power factor, voltage variation, and unbalance voltage) considering several standards and provides a proper and complete diagnosis of the power quality in electrical systems. In the proposed C-HFS-ADL each output of a subsystem is transferred between inner layers of the hierarchical system and a total power quality diagnosis is obtained taking into account a secondary decision-making process with additional defuzzification in order to have a partial diagnosis for each subsystem of the hierarchy. In addition, an algorithm was implemented considering different inference systems for analyzing the behavior of the C-HFS-ADL on a database (power quality indices) obtained from a real electrical substation for observing its advantages and disadvantages.
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