Topology Identification of Low-Voltage Distribution Networks Considering Hidden Errors

Accurate topology information is the key to supporting these requirements of coordinated operation of source-load-storage resource in low voltage distribution network (LVDN). The comprehensive coverage of smart meters provides a data basis for low-voltage topology identification (LVTI). However, due to electricity theft, PLC crosstalk, interruption of communication, the measurement data will be distorted, which will seriously affect the performance of LVTI methods. Thus, this paper defines the hidden errors and proposes a LVTI method based on layer-by-layer stepwise regression. Firstly, a multi-linear regression model for LVTI based on the energy conservation principle is established. Secondly, the significance factor according to F-test was proposed to modify the identification results considering hidden errors. Thirdly, the regression model and significance threshold parameters were iteratively updated layer by layer to improve the recall rate of the final identification results. Finally, the test system simulation of 63 users and practical application results show that the proposed method can ensure more than 90% of the precision rate under the influence of hidden errors, which has significant engineering application value.