RECOGNIZING ANIMAL-CAUSED FAULTS IN POWER DISTRIBUTION-SYSTEMS USING ARTIFICIAL NEURAL NETWORKS

Faults are likely to occur in most power distribution systems. If the causes of the faults are known, specific action can be taken to eliminate the fault sources as soon as possible to avoid unnecessary costs, such as power system down-time cost, that are caused by failing to identify the fault sources. However, experts that can accurately recognize the causes of distribution faults are scarce and the knowledge about the nature of these faults is not easily transferable from person to person. Therefore, artificial neural networks are used in this paper to recognize the causes of faults in power distribution systems, based on fault currents information collected for each outage. Actual field data collected by Duke Power Company are used in this paper. The methodology and implementation of artificial neural networks and, fuzzy logic for the identification of animal-caused distribution faults will be presented. Satisfactory results have been obtained, and the developed methodology can be easily generalized and used to identify other causes of faults in power distribution systems.