Abstract: This paper proposes a power quality disturbance classification technique based on the energy of the distorted signals. The multi-resolution analysis technique of DWT is employed on the distorted signals to extract the energy distribution features at different levels of resolution. To identify the different power quality disturbances the energy difference at each decomposition level is calculated with respect to the energy of the pure sinusoidal signal. Then probabilistic neural network is applied to classify the power quality disturbances. The simulation results validate the accuracy and efficiency of the proposed method.