Research On The Identification Method Of Topology Structure Of Low Voltage Distribution Network

Low-voltage distribution network is at the end of the power system,and its stable operation is the key to ensuring high power quality for users.The identification of lowvoltage topology is the basis for intelligent management of low voltage station area.The accurate topology structure provides important data support for distribution network applications,such as fault location,line loss management,and power theft detection.However,due to the expansion,reconstruction,operation adjustment of distribution network,the topology structure has the problem of inaccurate record.Manual investigation and recording of distribution network topology,which is not only costly but also low accuracy.At present,all kinds of intelligent monitoring terminals are used,which provides favorable conditions for topology identification.The voltage data preprocessing method is proposed to solve the problem of low accuracy of topology recognition when the voltage data is missing or the voltage change is not obvious.Newton interpolation method is used to process the missing data for the case of a small amount of voltage data for user is missing,then use Pearson correlation coefficient to identify the topology structure.When some of the voltage data of the users do not change significantly,the equal length sequence segmentation according to the experience or time series segmentation based on minimum points are used to extract the data,and then use the Pearson correlation coefficient to identify the station topology structure.The results of case analysis show that the Newton interpolation method is suitable for the recognition of the relationship between the user and the station area when there are few data missing;compared with the original data,the feature data extracted by the time series segmentation method has better topological recognition effect,and the method of extracting the data by the minimum point is more universal.A low-voltage topology automatic identification method based on gray correlation degree and K-nearest neighbor(KNN)algorithm is proposed to solve the problem that it is difficult to identify the household change relationship of users with weak correlation.First,the T-type grey correlation degrees of the voltages between the users and the station area are calculated,and the KNN algorithm is used to judge the suspicious users of a station area by the set threshold value to identify the relationship between the user and the station area.Then,the T-type grey correlation degrees between user voltages are calculated under the new station area,and the suspicious users in the feeder are identified by the topological structure diagram.Finally,the users related to the suspicious users are found,and the location of the suspicious users in the feeder is located according to the characteristic that the voltage decreases gradually along the feeder.After the low voltage topology is correctly identified,the parameter identification method of distribution circuit based on the least square method is proposed.Combined with other measurement data,the impedance parameters of the line are identified.The results of case analysis show that the proposed method has high accuracy and good practicability in low-voltage topology identification.