A Method Based On Wavelet Transform And Fourier Transform For Power Quality Analysis

With the rapid development of national economics and electricity markets, power quality issues have captured considerable attention from both utility companies and their customers in many countries, in part due to the proliferation of sensitive electronic equipment. A poor supply quality can degrade the quality of products, interrupt important industrial processes and therefore lead to economic losses. To improve the electric power quality, a monitoring and analyzing system must be established to detect, estimate and classify different disturbances. As a consequence, it must be supported by suitable measurement methods and apparatus. The paper presents an on-line measurement method based on wavelet transform and Fourier transform for power quality analysis in electric power systems. The comparison of wavelet denoising with low-pass filtering is performed before the wavelet is introduced as a pre-processing tool for power quality signals. The key of this paper is to detect and extract disturbances with multi-resolution analysis (MRA). The detection of the non-steady state disturbance and its duration are attained by a proper application, on the sampled and denoised signal, of the Mallat decomposition algorithm. And the modulus local maxima properties of the first-level and second-level detail versions can be used as a criterion to classify steady and non-steady state phenomena. The disturbance waveform is extracted by reconstructing, in an optimized way, the signal in frequency subbands by means of the MalIat reconstruction algorithm. To classify short-duration variations further, a program is designed so that sags, swells and interruptions can be identified exactly. As to steady state phenomena, the traditional signal analysis tool FFT is used for harmonic analysis, which is also conceived for a means to distinguish harmonic and flicker. The proposed method is characterized by its real-time property and it is designed for an agile disturbance classification. In the paper firstly the theoretical background of power quality phenomena is expounded. Secondly, three transform-based methods (Fourier transform, short-time Fourier transform and wavelet transform, respectively) and their applications are discussed. Then, the proposed method is described in detail. Finally, some case studies are examined in order to highlight the performance of the method.