Intelligent Identification System of Power Quality Disturbance

Studies of power quality phenomena have emerged as an important subject in recent years due to renewed interest in improving the quality of the electricity supply. Because the wide application of high-power electronics switchgear, problems of power quality are becoming more serious as each passing day. How to identify power quality disturbances from large number of power signals and how to recognize them automatically are important for further understanding and improving of power quality. In this work, we propose an intelligent system for detection and classification of power quality disturbance using wavelet transform and multi-lay support vector machines. The proposed technique allows creating such expert systems with the extensible knowledge base, which can be used for identification of power quality disturbances. The simulation result verifies its validity to classify power quality disturbances.