Topology Identification Method of Low-voltage Distribution Network Based on Improved Pearson Correlation Coefficient Method
Liwen Qin, Weixiang Huang, Zhicheng Guo, Yangjun Zhou, Bin Zhang · 2021 IEEE 2nd China International Youth Conference on Electrical Engineering (CIYCEE) · 2021
The traditional low-voltage network topology identification mainly relies on manual investigation, which has problems such as high cost and low recognition efficiency. Therefore, this paper proposes a low-voltage distribution network topology identification method based on the improved Pearson correlation coefficient method. First, the Kalman filter is used to filter the acquired voltage data sequence, highlighting the data characteristics, and paving the way for the calculation of correlation coefficients. Then, the Pearson correlation coefficient between all the units that need to be judged is calculated. Finally, according to the set coefficient threshold value, the station area is identified. Compared with existing methods, this method can use limited data to accurately identify the user's station area, with high accuracy and good practicability. Based on MATLAB/Simulink, a typical 13-node topology network in the station area was built, which showed the effectiveness of the method.