This paper presents an approach that is able to provide the detection and location of power quality disturbances and the identification of type of power quality problems. Wavelet transformation (WT) is a mathematical tool used for signal processing which is better than short time Fourier transforms (STFT). The proposed algorithm uses different kind of wavelets, each for a particular class of disturbance[1]. The given signal is decomposed through wavelet transform and any change in the smoothness of the signal can be detected at the finer wavelet transform resolution levels. Each power quality disturbance has unique deviations from the pure sinusoidal waveform and this is adopted to provide a reliable classification of the type of disturbance. A qualitative comparison of results will show the advantages and drawbacks of each wavelet when applied to the detection of the disturbances. This method is tested for a large class of test conditions simulated in MATLAB. A few power signals with power quality disturbances have been analyzed to show the effectiveness of the proposed technique. Power quality monitoring with the ability of the proposed algorithm to classify the disturbances will be a powerful tool for the power system engineers.