An Advanced Hybrid Solution for Automated Substation Monitoring Using Neural Nets and Expert System Techniques

This paper describes a new solution for an automated analysis of the substation equipment operation during fault disturbances. An expert system, developed earlier for automated analysis of digital fault recorder (DFR) files, is the basis for the new solution. The expert system makes an analysis based on outputs of the signal processing algorithms used to calculate waveform parameters for the faulted transmission line. The new solution utilizes neural nets to perform both fault detection and classification for a given transmission line. Therefore, the signal processing and a part of the fault analysis expert system logic are substituted in the new solution with the neural nets. The paper discusses constraints of the earlier solution, gives details of the new implementation, and provides summary of the benefits as well as the test results obtained using EMTP simulations.