Issue |
E3S Web Conf.
Volume 185, 2020
2020 International Conference on Energy, Environment and Bioengineering (ICEEB 2020)
|
|
---|---|---|
Article Number | 01045 | |
Number of page(s) | 5 | |
Section | Energy Engineering and Power System | |
DOI | https://doi.org/10.1051/e3sconf/202018501045 | |
Published online | 01 September 2020 |
Research on topology identification technology of distribution station area based on distribution Transformer supervisory Terminal Unit
1 NARI Technology Co., Ltd, Nanjing City, Jiangsu province, China
2 Nanjing Normal University, Nanjing City, Jiangsu province, China
This paper proposes a topology identification idea based on the physical equipment and information fusion of the distribution network, which fully combines existing distribution automation master stations, intelligent distribution transformer terminals, smart meter equipment and information data resources, and uses carrier communication technology to reflect the topological relationship of the distribution station area, carry out research on key technologies of distribution network topology identification, in order to realize the comprehensive integration identification of the distribution station-linetransformer-household relationship and the distribution network topology structure, and improve data penetration between different systems ability to provide basic support for intelligent and lean operation and maintenance of the distribution network.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.