الفهرس 
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Abstract
Power Quality is becoming an issue of increasing concern both to the utilities and their customers. A power quality problem can be best described as any variation in the electrical power service, such as voltage sags and swells, interruptions, transients, harmonics, notches, and fluctuations, resulting in misoperation or failure of end-use equipment. The aforementioned disturbances, degrading the reliability and quality of the power supply, though always existed on utility systems, are nowadays causing more and more troubles. This is due to the increased refinement of today’s automated equipment, such as variable-speed drives, automated production lines, programmable logic controllers, and power supplies in computers. They are far more sensitive to disturbances on the utility system than previous generation of electromechanical equipment and less automated production and information systems.
To improve the electric power quality, sources of disturbances must be known and controlled. This can be done by first detecting, localizing, and classifying different disturbances. To achieve this, a sensor-based on-line monitoring device is necessary. A feasible approach to satisfy this goal is to use a powerful tool that has the ability to analyze different power quality problems simultaneously in both time and frequency domains.
To analyze these electric power system disturbances, data is often available as a form of a sampled time function that is represented by a time series of amplitudes. When dealing with such data, the Discrete Fourier Transform (DFT) based approach is most often used. The implementation of the DFT by various algorithms has been constructed as the basis of modern spectral and harmonic analysis. The DFT yields frequency coefficients of a signal, which represents the projection of orthogonal sine and cosine basic functions. Such transforms have been successfully applied to stationary signals where the properties of the signals do not vary in time. However, for non-stationary signals, any abrupt change may spread all over the frequency axis. If a signal is altered in a localized time instant, the entire frequency spectrum can be affected. The Short Time Fourier Transform (STFT) uses a (time-frequency) window to localize in time sharp transitions. However, the STFT uses a fixed time-frequency window, which is inadequate for the practical power system disturbances encountering a wide range of frequencies. Under this situation, the Fourier techniques are less efficient in tracking the signal dynamics. Therefore, an analysis adaptable to non-stationary signals is required instead of Fourier-based methods.