Time-Frequency Analysis Techniques for Detection of Power System Transient Disturbances

The transients in power system cause serious disturbances in the reliability, safety and economy of the system. The transient signals are the transitory (short term duration) for which the frequencies as well as varying time information are compulsory for the analysis purposes. These disturbances occur for few cycles, which are difficult to be identified and classified by digital measuring and recording instrumentations. In digital signal processing, fast Fourier transformation (FFT) is a powerful technique, utilized to measure the signals. This technique is more suitable for periodic analys is where time information of the signal is not necessary. Various types of transients indicate various behaviors and measuring characteristics but it is vital, first to detect and classify the type of fault and then to mitigate them. This proposal suggest s that transient signals can be detected and analyzed with the help of discrete wavelet transformation (time-frequency) with multiresolution analysis (MRA) algorithm and Daubechies as mother wavelet. This proposed methodology possesses the ability to de -noise and decompose the various types of transient using Matlab/Simulink and Wavelet toolbox and the simulation results prove their simplicity, accurateness and effectiveness for the detection of power system transient signals.