An Algorithm for Diagnosis of Faults and Power Quality Problems in Radial Distribution Networks

This paper presents a methodology for diagnosis of faults and power quality problems in primary distribution feeders. The input data are the currents of the feeder per phase, monitored only in the substation. An artificial immune system was developed using the negative selection algorithm to detect and classify the faults and power quality problems. The main application of the software is to assist in the operation during a fault and supervise the power quality problem. A 103-bus non-transposed real feeder is used to evaluate the proposed algorithm. The results show that the algorithm is effective in its proposed and it has great potential for on-line applications.