Application Of Wavelet (Package) Transform In Power Quality Analysis

With wide application of large number of non-linear electric elements in power system, the detection research of power quality problem has become one of the most important subjects in power system. Effective detection, classification and statistics of the transient phenomena of the waves plays an important role in recognizing so many factors that affect the power quality and tracking the related causes and improving the power quality. The paper gives research on noise elimination of the disturbing signals and classification of the power quality disturbances, which mainly contains the following parts:Large amount of noise included in the power quality signals may greatly affect the results of detection in the power system. Based on cross validation criterion , a new method to suppress the white noise in power quality signals is proposed in this paper. The method can select the optimal threshold value via cost function of Integrate Square Error (ISE) without estimating any parameter of background noise.Thus it can solve the intrinsic difficulty of selecting the wavelet function during the decomposion and the effect is better than that of traditional methods. The simulation results prove the validity of the method in extracting abrupt information, improving the Signal-to-Noise-Ratio (SNR).Furthermore, the de-noised power quality signal's Square Error (SE) is fairly low.Based on Singular Value Decomposition and Least Square Support Vector Machines,the paper proposed a new method of recognizing the type of the power quality disturbance.The method decomposed the fundamental frequence, the disturbance frequence and the noises into different orthogonal characteristics subspace by SVD of the coefficient matrix from the Wavelet Package Transformation ; then used them to make devision with Singular Value of normal voltage to cancle the effect of niose energy, displayed the tiny differences among different disturbance types as much as possible. And then it used them as the input parameters of the LS-SVM,to realize the recognition of the power quality disturbance type. Simulation results indicate that the method has good performance of accuracy and stability,and is immune to the effect of noises.