Research On Classification Of Transient Power Quality Disturbances In Active Distribution Networks Based On RTDS

With the increasing requirements for energy saving,emission reduction and energy efficiency,more research is focused on the generation of renewable and clean energy such as wind energy and solar energy.Distributed new energy power generation technology has been rapidly developed,and the concept of active distribution network is also presented and perfected.With the application of a large number of power electronic devices and nonlinear sensitive loads in active distribution networks,more complex power quality issues affect the safe and stable operation of active distribution networks.Therefore,comprehensive,accurate and effective detection and identification analysis of the power quality in the active distribution network has very important theoretical and practical significance.Based on the RTDS / RSCAD real-time digital simulation platform,this paper first builds an active distribution network simulation model based on doubly-fed induction generator system for wind power grid connection and single-stage grid-connected photovoltaic power generation grid connection,and obtains the active distribution network Internal transient power quality disturbance signal,including transient oscillation disturbance caused by grid connection of distributed power in active distribution network,disturbance data such as voltage swell,voltage sag and voltage interruption caused by short circuit fault of public node The research and analysis of the transient power quality of the power grid provides the data basis.In the research of transient power quality disturbance detection algorithm,aiming at the problem of modal aliasing existing in the analysis of disturbance signals with large time scale in traditional empirical mode decomposition,an improved wavelet threshold denoising and K value pre-test VMD are proposed.Transient power quality testing.The Hilbert spectrum analysis based on the algorithm in this paper is used to analyze and detect the Matlab simulation signal and the electromagnetic transient disturbance signal of the active distribution network.Compared with HHT and other methods,it has higher signal decomposition performance and detection accuracy.In the research of transient power quality disturbance recognition algorithm,in view of the problem that the current transient power quality recognition classification accuracy is not high,a power quality composite disturbance classification method based on VMD multi-scale permutation entropy and QPSO-RVM is proposed.This method combines VMD decomposition to extract the perturbation multi-scale permutation entropy as the feature quantity of the perturbation signal.The quantum particle swarm optimization algorithm is used to optimize the RVM parameters.Finally,the extracted feature vector is input to the QPSO-RVM as a classifier for perturbation recognition and classification.In MATLAB,the algorithm of this paper is used to classify and recognize 6 single disturbance signals and 6 double composite disturbance signals.The recognition performance of the method using different types of feature vectors and classifiers is analyzed and compared,and the classification and recognition methods proposed in this paper are verified by simulation.It has the advantages of high accuracy and strong noise resistance.In order to verify the universality of the algorithm in this paper in a more complex active distribution network,based on the establishment of distributed power supplies in Chapter 2,simulations are obtained for various situations of DG grid connection,short circuit fault,grid connection and island switching corresponding disturbance data,and then using the power quality disturbance detection and recognition methods described in Chapters 3 and 4 to analyze the simulation data,all verify the validity and accuracy of the proposed algorithm in more complex system.This paper has 80 figures,15 tables and 98 references.