Characterization of Various Power Quality Disturbances Based on Signal Processing and Artificial Intelligence Scheme

Abstract

These days the electrical power quality has become a vital issue for the utilities and the consumers. Use of non-linear and sensitive loads add gradual deterioration of power quality. To improve power quality, automatic classification of power quality disturbances(PQDs) is much essential, which are also important for protection of transmission system network. Disturbances are mostly transient and temporary, thereby necessitate suitable method to analyze PQDs. In this paper a combined technique in the form of wavelet transform(WT) in association with fuzzy expert system is used for characterizing PQ disturbances. A no. of PQ signals are developed and decomposed using WT method for nearly exact detection of disturbances. Energy and Total Harmonic Distortion (THD) of all PQ disturbances are extracted through discrete wavelet transform (DWT) and are used in the fuzzy expert system to detect and classify different disturbances accurately. The fuzzy system used classifies the disturbances and confirms the presence of harmonics.