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A Wavelet-Fuzzy Logic Based System to Detect and Identify Electric Power Disturbances

In this paper a method to detect and classify typical electric power disturbances is presented. Voltage sags, swells, momentary outage and capacitor switching transient events (CSTs) are the electric disturbances considered in this work. Disturbance detection and some disturbance features are obtained by the discrete wavelet transform. These features are used in the design of a fuzzy rule classification system. Both methods, wavelet detection and the fuzzy classifier, are extensively tested on the detection and classification of several simulated electric disturbances. In particular, capacitor switching transients events (CSTs) are presented to validate the proposed methodologies. The performance of the wavelet-fuzzy logic system turned out to be 95% of correct identification. The performance of the fuzzy classifier outperforms a classifier based on crisp decisions also presented in this paper. This performance is acceptable compared with other methodologies reported in the literature with performances varying from 92% to 95%