An Intelligent-based Islanding Detection Method Using K-Nearest Neighbors and Discrete Wavelet Transform

In this paper, a method for islanding detection based on analysis of transient state signals is provided. K-Nearest Neighbors (KNN) is trained for classifying the transient events. The required features for classifying are extracted through DWT of signals. The proposed method is then simulated on a medium voltage distribution system of CIGRE with two kinds of DGs using DIgSILENT, MATLAB and WEKA softwares. By analysis performed on type of input signal, type of mother wavelet and required transform level, among 162 relay designs, an optimum relay was selected for DGs based on accuracy, speed, simplicity and cost parameters. By evaluation, it was determined that using only one input (voltage) signal not only improves speed and simplicity and reduces costs, also makes accuracy of the proposed relay better than other intelligent and passive methods.