Optimal Setting of Drift Parameters Using Differential Evolution for Performance Enhancement of Fault Detection Scheme.

Fault detection schemes become more dependable with the proper selection of drift parameters. In this paper, a new approach is presented to set such drift parameters using a differential evolution algorithm. These optimally selected drift parameters are incorporated in a superimposed current-based fault detection scheme to enhance its performance and nullify the use of additional threshold settings. Later, the performance of fault detection schemes with optimal drift parameters is compared with regular drift parameters by generating data on a two-bus test power system. The results clearly show that the optimally generated drift parameters enhance the performance of the fault detection scheme and are also used for faulty phase identification. [ABSTRACT FROM AUTHOR]