On-line power system fault estimation using connectionist models

This paper proposes a new connectionist (or neural network) expert diagnostic system for online fault diagnosis of a power substation. The connectionist expert diagnostic system has a similar profile to an expert system, but can be constructed much more easily from elemental samples. These samples indicate the associations of faults with their protective relays and circuit breakers, as well as the bus voltages and feeder currents. Through an elaborately designed structure, these two types of alarm signals are processed by different connectionist models. The outputs of the connectionist models are then integrated to provide the final conclusion with a confidence level. The proposed approach has been practically verified by testing on a typical Taiwan Power (Taipower) secondary substation. The test results suggest that this system can be implemented by various electric utilities with relatively low customization effort