Power Quality Analysis Method Of Wind Power Integration Based On Wavelet Packet Denoising

With the development of wind power technology,more and more wind farms will be integrated into the power grid.The integration of wind farms into the power grid increases the proportion of renewable energy in the system,and it also leads to more and more complicated power quality problems.One of the important factors in wind power installed capacity which needs to be considered is the power quality problem.Only by reducing its impact on the system to a certain standard,so that can we ensure the security and stability of the system and the benign development of wind power generation.Therefore,it is necessary to study the power quality problems and the related analysis methods of wind farm connected to the power grid.The main research contents of this paper can be discussed as follows:(1)The influence of wind turbine generator grid on power quality of power grid.Several power quality problems of wind power grid are summarized in the respect of wind farm and grid.such as voltage fluctuation,harmonic,voltage deviation,voltage sag,etc.I analyze the reasons and mechanism of the power quality caused by the wind power unit's integration into the power grid,at the same time,the simulation signal model of various power quality problems is given.This paper introduces the data source of power quality disturbance signal of wind power grid connected with wind farm SCADA system in Chenzhou wind farm.(2)The Study on signal denoising method of power quality disturbance signal in wind power grid connection.The denoising simulation of wavelet and wavelet packet is carried out,it can be judged that the denoising effect of wavelet packet is better than that of wavelet denoising by contrast.the wavelet packet is further studied,and then the wavelet packet basis function with better indexes is selected,which is used to denoise the research of different decomposition layers of the wavelet packets with the noise signal,The optimal denoising function and the optimal decomposition layer can be selected from 4 different wavelet packet basis functions.The simulation results show that the sym4 wavelet packet basis function has the best denoising effect when the five layers are decomposed.(3)Power quality disturbance start-stop time detection based on lifting Db4 complex wavelet transform.The principle and advantages of complex wavelet are explained in this chapter,compared to the real wavelet transform,the complex wavelet transform contains more information.including the amplitude and phase information of the disturbance signal.which has more advantages in the detection of power quality signal.The lifting format algorithm is applied to the complex wavelet transform in this chapter,and a method for detecting power quality disturbance based on the lifting db4 complex wavelet transform is proposed.The simulation results show that the operation efficiency and precision of the lifting wavelet transform are better than the real wavelet transform and the complex wavelet transform,and the detection time is less,the error is smaller and the efficiency is higher.(4)The power quality disturbance classification of wind power grid connection based on the optimized support vector machine.It proposes the wavelet packet transform to extract the eigenvalue of disturbance signal aim at the identification of power quality disturbance signals in wind power grid in this chapter.In the next the particle swarm optimization algorithm(PSO)is proposed to optimize the parameters of SVM kernel function,which is used to identify disturbance signals.Aiming at the typical disturbance signal,different classification methods are used for disturbance recognition experiments for typical disturbance signals.The simulation results show that the PSO-SVM classifier is more accurate than the SVM classifier.