Recognition of Power Quality Disturbances Using Discrete Wavelet Transform and Fuzzy C-means Clustering

This paper is focused to present an approach based on discrete wavelet transform (DWT) and Fuzzy c-means clustering (FCM) for detection and classification of the power quality (PQ) events. PQ disturbances are simulated in MATLAB with the help of mathematical expressions. PQ disturbances such as voltage sag, voltage swell, momentary interruption (MI), oscillatory transient (OT), impulsive transient (IT), harmonics, notch and spike are investigated in the proposed study. Discrete wavelet transform based plots up to fourth level of decomposition of the voltage signal with PQ disturbance are used for recognition of the PQ events. DWT based features have been given as input to FCM clustering for classification purpose of PQ events. It is observed that proposed algorithm is effective in the detection as well as classification of investigated power quality events. Proposed approach is implemented using the MATLAB codes.