A Decision Making Methodology to Assess Power Quality Monitoring Index of an AC Microgrid Using Fuzzy Inference Systems

Abstract The power quality issues are challenging in microgrid due to the presence of various types of renewable energy resources unlike conventional power system. So, the main objective of this research is to quantify the power quality considering the fuzziness in variation of voltage, frequency, power factor and total harmonic distortion (THD) due to the occurrence of voltage sag, swell, interruption and unbalancing in three-phase AC microgrid feeding static and rotational loads. Therefore, a novel power quality monitoring index (PQMI) is proposed to determine the status of power quality. Total 256 numbers of rules are formed for fuzzy inference system (FIS) to assess PQMI considering the acceptable limits of above mentioned four input variables as per IEEE/IEC standards. The proposed methodology is verified through Mamdani and Sugeno type FIS using Matlab-Simulink software. It is also found that the proposed PQMI is significant to define the status of microgrid even during transition from grid-connected to islanded mode and vice-versa.

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