Application of Kalman Filtering in Computer Relaying

Abstract

During the first cycle following a power system fault, a high speed computer relay has to make a decision usually based on the 60 Hz information, which is badly corrupted by noise. The noise in this case is the nonfundamental frequency components in the transient current or voltage, as the case may be. For research and development purposes of computer relaying techniques, the precise nature of the noise signal is required. The autocorrelation function and variance of the noise signal was obtained based on the frequency of occurrence of the different types of faults, and the probability distribution of fault location. A new technique for modelling the signal and the measurements is developed based on Kalman Filtering theory for the optimal estimation of the 60 Hz information. The results indicate that the technique converges to the true 60 Hz quanitities faster than other algorithms that have been used. The new technique also has the lowest computer burden among recently published algorithms and appears to be within the state of the art of current microcomputer technology.