This paper deals with two new methods,based on k-NN algorithm,for fault detection and classification in distance protection.In these methods,by finding the distance between each sample and its fifth nearest neighbor i...This paper deals with two new methods,based on k-NN algorithm,for fault detection and classification in distance protection.In these methods,by finding the distance between each sample and its fifth nearest neighbor in a predefault window,the fault occurrence time and the faulty phases are determined.The maximum value of the distances in case of detection and classification procedures is compared with pre-defined threshold values.The main advantages of these methods are:simplicity,low calculation burden,acceptable accuracy,and speed.The performance of the proposed scheme is tested on a typical system in MATLAB Simulink.Various possible fault types in different fault resistances,fault inception angles,fault locations,short circuit levels,X/R ratios,source load angles are simulated.In addition,the performance of similar six well-known classification techniques is compared with the proposed classification method using plenty of simulation data.展开更多
文摘This paper deals with two new methods,based on k-NN algorithm,for fault detection and classification in distance protection.In these methods,by finding the distance between each sample and its fifth nearest neighbor in a predefault window,the fault occurrence time and the faulty phases are determined.The maximum value of the distances in case of detection and classification procedures is compared with pre-defined threshold values.The main advantages of these methods are:simplicity,low calculation burden,acceptable accuracy,and speed.The performance of the proposed scheme is tested on a typical system in MATLAB Simulink.Various possible fault types in different fault resistances,fault inception angles,fault locations,short circuit levels,X/R ratios,source load angles are simulated.In addition,the performance of similar six well-known classification techniques is compared with the proposed classification method using plenty of simulation data.
