关键词: 电能质量, 扰动识别, 小波能量差, 支持向量机, 邻域粗糙集

Abstract:

It proposes a method to identify Power Quality Disturbances（PQD） based on wavelet energy difference distribution and Support Vector Machine（SVM）.It uses wavelet transform to analyze PQD signals，extracts disturbance duration time and energy differences of every level between PQD signal and standard signal as feature vectors，forms the training samples and testing samples.It preprocesses the training set by using neighborhood rough set model to delete those abnormal samples and disturbances.It traines the PQD samples by using Binary Tree SVM（BT-SVM） to identify PQD signals.Testing results indicate that the proposed method can identify seven PQD signals and sinusoidal signal，has an excellent performance on correct ratio（the average ratio can reach 97 percent），has high identification speed and strong resistance to noise，and is very suitable for PQD identification system.

Key words: power quality, disturbance identification, wavelet energy difference, support vector machine, neighborhood rough set