Research On Power Quality Signal Reconstruction Algorithm Based On Compressed Sensing

With the continuous development and progress of science and technology,smart grid has become the only way for the development of power grid technology.Safe,reliable and stable operation of power grid is an inevitable requirement of smart grid,which undoubtedly improves the requirement for obtaining high-quality power quality signal data of the grid.In view of the advantages of Compressed Sensing theory in compression sampling,this thesis deeply studies the theory of Compressed Sensing,and focuses on the reconstruction algorithm.and proposes A reconstruction algorithm based on Compressed Sensing is proposed and applied to the reconstruction of power quality signals,which achieved a good reconstruction effect.Based on the in-depth study of the greedy matching pursuit algorithm,aiming at the shortage of the high number and the high misclassification rate in the candidate set atom initial selection by the Compressed Sampling Matching Pursuit algorithm,the threshold selection strategy is given to complete the preliminary selection process of the candidate set atoms in the manner of threshold selection,which reduces the burden for the atomic cutting of the backtracking process and reduces unnecessary reconstruction work.Aiming at the shortage of the principle that the Compressed Sampling Matching Pursuit algorithm determines the completion of reconstruction with a fixed number of cycles,which will increase the unnecessary reconstruction time,there is not strong adaptability to the actual application,the correlation degree judgment strategy is given to determine the algorithm reconstruction by the correlation change between the perception matrix and the residual between adjacent iterations,which effectively reduces unnecessary iterations and improves the reconstruction efficiency of the algorithm.The Modified Compressed Sampling Matching(MCSMP)Pursuit algorithm is proposed.The algorithm selects the atoms of the candidate set by the threshold selection strategy,then uses these atoms to estimate the sparse signal,selects the signal with high contribution to the estimated signal,and uses the correlation judgment strategy to determine the algorithm reconstruction.The algorithm improves the performance of the algorithm by increasing the proportion of correct atoms involved in the reconstruction and reducing unnecessary reconstruction work.The characteristics of power quality disturbance signal are analyzed in detail.According to its characteristics,Fourier transform is used as the sparse transform base.Gaussian random matrix is used to reduce the dimensionality of the disturbance signal,and the Modified Compressed Sampling Matching Pursuit algorithm is applied to the reconstruction of power quality disturbance signals.The simulation results show that compared with the similar greedy matching pursuit algorithm,whether in the reconstruction performance index or reconstruction speed,MCSMP algorithm all show better performance advantages.