Digital System for Detection and Classification of Power Quality Disturbances

This paper presents a new method for detection and classification of power quality disturbances which achieves good performance with low computational cost. The event detection is based on the analysis of the statistical properties of the error signal which is defined as the difference between the sampled signal and its fundamental sinusoidal component, generated by the proposed algorithm. The classification is performed using a multi-rate technique for features extraction over the error signal and a multilayer feed-forward neural network. Numerical results from computational simulation showed the good performance of the proposed method.