Novel approach for fault diagnosis of the power grid with information fusion of multi-data resources

The fault information mainly consist of two parts, the digital part and the analogue one, when the power grid is malfunctioning. The digital information reflects the status of relays and circuit breakers by which most methods for fault diagnosis utilize this information. The analogue information is about the transient value and the wave of voltage and current. The analogue information can accurately describe the properties of failure in the power grid. However, few methods for fault diagnosis use this data resource. A new fault diagnosis method, i.e. information fusion of multi-data resources in fault diagnosis based on improved D-S theory (IMFD) with digital and analogue information is presented. The digital information is transformed to fuzzy fault degree through fuzzy Petri nets and the analogue information is transformed to wavelet fault characteristics through the wavelet analysis. Then fault diagnosis is conducted based on information fusion with the improved D-S evidence theory. Finally, the fault element is identified with C-mean algorithm. Simulation results indicate that the proposed method can improve the accuracy and the real-time performance of fault diagnosis in the power grid. © 2009 Chin. Soc. for Elec. Eng.