Fault locating methods for radial distribution systems - Zuñiga, Davidjohn A.
Radial distribution systems are at risk to various short-circuit faults that cause power outage and lead to loss of revenue for the distribution utility and service interruption for their customers. The current practice for locating faults is to send linemen to trace where the fault might have occurred. Even though proven, it is an inefficient and time-consuming way to locate faults. This project applies the concepts of short circuit calculations based on both sequence and phase frames of reference to produce values (i.e., phasor currents, distance to fault, and type of the fault) that are used to train an artificial neural network (ANN) to locate faults on a radial distribution system. The capability to locate faults was tested using the IEEE 13 Node Test Feeder and IEEE 123 Node Test Feeder. Results from the two tests were then analyzed and compared with the target outputs; once the error of the results to the target outputs were acceptable, the methods were then used to locate faults for an actual radial distribution system. Testing of the developed methods on an actual distribution system was done by using the data provided by the Benguet Electric Cooperative (BENECO).