AUTHOR=Tong Li , Chai Weijian , Wu Dongqi 

TITLE=Topology and Impedance Identification Method of Low-Voltage Distribution Network Based on Smart Meter Measurements

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.895397

DOI=10.3389/fenrg.2022.895397

ISSN=2296-598X

ABSTRACT=In recent years, Distributed photovoltaic facilities and distributed energy storage are widely connected to low-voltage distribution network, which makes the topology of low-voltage distribution network change faster, and the online identification and monitoring of the impedance of each branch becoming more difficult. With the widespread installation of new distribution automation terminals and smart electricity meters, the technical gap of power data collection has been filled, the state perception ability of distribution network has been improved, and the data support for further exploration of the topology and impedance of distribution network has been provided. 
Therefore, based on a data-driven low-voltage distribution network topology and impedance identification method, a physical topology model of distribution transformer-branch-meter box - user and a impedance exclusion model are established. Line loss and branch node power flow are calculated on the basis of the two models. Finally, the low voltage distribution network topology recognition algorithm and power flow partition backtracking impedance estimation technology are developed based on the data mining method of distribution transformer terminal and smart meter.  
The example results show that the physical topology model of distribution transformer-branch-meter box-user and the impedance exclusion model proposed in this paper can effectively identify the branch topology and impedance distribution in the low-voltage distribution network with a large amount of measurement information, realize the online perception of the distribution network, and provide the basis for the fine management of the power grid and the management of line loss.