Recognition of Complex Power Quality Disturbances Using Discrete Wavelet Transform and Fuzzy C-means Clustering
DOI:
https://doi.org/10.26438/ijcse/v6i9.225236Keywords:
Power Quality, Complex power quality disturbance, Discrete wavelet transform, Fuzzy C-means clusteringAbstract
This paper's approach based on discrete wavelet transform and Fuzzy c-means clustering for the detection and classification of the complex power quality disturbances. The complex power quality disturbances have been generated in MATLAB by various combinations of the mathematical models single stage power quality disturbances such as voltage sag, voltage swell, momentary interruption, oscillatory transient, impulsive transient, harmonics, notch and spike. The investigated complex power quality disturbances are (voltage sag + harmonics), (voltage swell + harmonics), (momentary interruption + harmonics), (oscillatory transient + voltage sag), (oscillatory transient + harmonics), (impulsive transient + voltage sag), (Impulsive Transient + harmonics) and (oscillatory Transient, Voltage Sag and Harmonics). The DWT based plots up to fourth level of decomposition of the voltage signal with complex PQ disturbance are used for the recognition of the complex PQ disturbances. The DWT based features have been given as input to the Fuzzy c-means clustering for classification purpose of the complex PQ disturbances. It is observed that the proposed algorithm is effective in the detection and classification of the complex power quality disturbances. The proposed approach has been implemented using the MATLAB codes.
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