Identification of Power Quality Disturbances Based on FFT and Attribute Weighted Artificial Immune Evolutionary Classifier

Abstract

Nowadays, the issue of Electromagnetic Compatibility is of great importance and urgency. In this paper, we propose a novel hybrid automatic identification system for power quality disturbances, which lays foundations for further analyzing the electromagnetic compatibility. Specifically, we firstly extract features by using the FFT and envelope detection method. Then we utilize the attribute weighted artificial immune evolutionary Classifier (AWAIEC) for classification of power quality disturbance events. Experimental results have shown that the proposed method performs better than existing approaches.