Identification and Classification of Multiple Power Quality Disturbances Using a Parallel Algorithm and Decision Rules

A multiple power quality (MPQ) disturbance has two or more (PQ) disturbances superimposed on a voltage signal. compact and robust technique is required to identify classify the MPQ disturbances. This manuscript investigated hybrid algorithm which designed using parallel processing of with stockwell transform (ST) hilbert (HT). will reduce computational time disturbances, makes fast. identification index (IPI) computed statistical features extracted from signal ST HT. IPI different patterns for various types effectively location (IPL) IPL identifies initiation end PQ thereby locates events respect time. Classification performed decision rules in both noise-free noisy environments 20 dB noise ratio (SNR). The performance proposed HT rule-based tree (RBDT) better compared RBDT techniques terms accuracy classification MATLAB software used perform study.