Verification method of topological relationship of low voltage distribution equipment based on KNN and Pearson correlation coefficient

Due to the characteristics of multiple points, complex users, and frequent changes, the topological relationship of the low-voltage distribution network is often in an inaccurate stage. The relationship between the inaccuracy of file information and the changes of registered permanent residence is the main problem to be solved. Therefore, based on the machine identification information, this paper studies the verification technology of the relationship between the three remotes data of distribution equipment and topological links. Firstly, the Pearson correlation coefficient and neighborhood algorithm are used to verify the topology of the low voltage distribution network. Secondly, this paper combines K-Nearest Neighbor (KNN) clustering and K-means to analyze the training sample set to obtain the best matching combination. Finally, the station area to be verified is selected. Based on the verification principle of the household-transformer relationship, the Pearson correlation coefficient is used to calculate the voltage data of the smart meter of users. The experimental results show that this method can improve the computational efficiency of the process, get the correct classification results, classify users in the overlapping area, and implement a topology check.