Research on a Time Plane Based Algorithm for Identification of Distribution Network Line Parameters

• Published in: IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (Online) Vol. 7; pp. 1311 - 1315
• Main Authors: Zhang, Jianwen, Geng, Jin, Liu, Fei, Liang, Jing, Wang, Hui, Liu, Hanming
• Format: Conference Proceeding
• Language: English
• Published: IEEE 15.03.2024
• Subjects: Adaboost algorithm; distribution network; Distribution networks; line loss; line parameters; Loss measurement; Mathematical models; Network topology; Parameter estimation; Power measurement; Voltage measurement; voltage phase angle
• ISSN: 2689-6621
• DOI: 10.1109/IAEAC59436.2024.10503950

Accurate line parameters are an important foundation for refined regulation and protection setting of distribution networks. In recent years, the topology of the circular distribution network, which has gained practical promotion, is complex and the direction of power flow is variable, making it difficult to apply the traditional radial network method for identifying line parameters. In this paper, a "time plane" based algorithm for identifying distribution network line parameters is proposed. In response to the situation where some distribution networks cannot collect voltage phase angle information from all nodes, it is proposed to analyze the power and voltage data that can be obtained by existing measurement equipment in the distribution network, and use a digital way to reflect the physical system to achieve visualization of the distribution network topology structure and line parameters. To achieve this goal, firstly, based on multiple sets of measurement data under time cross-sections, a linear regression topology and line parameter identification model is established according to the power flow equation, and preliminary calculations are made; Secondly, based on the concept of "electricity consumption", the line loss is used to infer the line parameters for each segment; Finally, the Adaboost algorithm was used to fuse the parameter identification results of the "time plane" and obtain the final distribution network parameter identification results. The feasibility of this method was verified using an IEEE 33 node example.