Research On Detection And Location Of Voltage Sink Based On HHT And APSO-RBF

With the rapid development of China’s economy,users’ requirements for power quality are gradually improving.Voltage sag is the most serious power quality problem.To solve the problem of voltage sag,the first thing to do is to detect the voltage sag.The accurate start and stop time and temporary drop value can be obtained through detection to better solve the problem of temporary sag in the future.Then the voltage dips source is located,the accurate location of the voltage dips source can solve the problem of temporary dips.This paper mainly studies the voltage dip detection algorithm and dip source location method.This paper introduces and analyzes several existing voltage sag detection methods,such as wavelet analysis method,fundamental component method,effective value detection method,instantaneous reactive power dq0 transformation method and single-phase voltage transformation average method,and illustrates the advantages and disadvantages of each method.Because these flaws real-time performance of the voltage sag detection method,is proposed in this paper,based on CEEMD HHT transform algorithm,compared with traditional EMD decomposition effect,obvious CEEMD decomposition effect is better,has set up a simulation platform for the 9 nodes distribution network,the test results verify that the algorithm can correct judgment when sag and temporary decline in value.This paper introduces the traditional locating method of voltage sag source,analyzes its theory and locating criterion.In view of the traditional voltage sag source location,the IEEE33-node distribution network model built by Simulink is used to carry out the voltage sag source location simulation verification.It is found that the traditional voltage sag source location method has defects.In the case of voltage sag caused by different fault types,there is inevitably a situation of misjudgment of location.In this regard,APSO optimization RBF neural network classification method.The characteristic quantity of traditional positioning method was taken as the input of the neural network,and 120 groups of characteristic quantity were obtained by simulation.90 groups of data were selected from the training set,and the remaining 30 groups were used as the test set.Simulation results show that the proposed method has high accuracy and can realize the location of voltage sag source.