Signal Sampling In Substation And Fault Analysis Based On Wavelet Transform

Substation is very important in power transmission and transformation system. Substation automation has some functions such as supervisory control and protection for main equipment and transmission or transformation line, as well as communication with control center. So, as the main ways of information source in substation automation, data acquisition has a very important value to study. On the other side, it should be find and remove the fault in time in the power system in order to guarantee the smooth manufacturing and life.In this paper, data acquisition methods in substation have been studied. DSP was adapted to complete AC sampling. In the case of power system, real time performance is needed. DSP has a lower cost and good real time performance.Wavelet analysis is a kind of method to process non-stationary signal in these years. Having good time-frequency localization character, and correctly identifying singularity point in fault signal, Wavelet is the main analysis method in this paper.Fast wavelet transform was explained in order to applying wavelet methods in real time system. A kind of fast algorithm was given in this paper and it has the same efficiency as Mallat algorithm.In this paper, Lipschitz exponent method was applied to identify the singularity in power system fault signal analysis and a simulation example was given in the last chapter. A de-noise example was list to explain how to remove noise from signal.