Recognizing animal-caused faults in power distribution systems using artificial neural networks

Abstract
Artificial neural networks are used to recognize the causes of faults in power distribution systems, based on fault currents information collected for each outage. Actual field data are used. The methodology and implementation of neural networks and fuzzy logic for the identification of animal-caused distribution faults are presented. Satisfactory results are obtained, and the developed methodology can be easily generalized and used to identify other causes of faults in power distribution systems.