Open AccessKnowledge graph‐based method for identifying topological structure of low‐voltage distribution network
Author(s) -
Zepu Gao,
Yongjian Luo,
Ziwei Xu,
Yilan Yu,
Lianmei Zhang
Publication year - 2020
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.1319
Subject(s) - computer science , topology (electrical circuits) , data mining , graph , transformer , identification (biology) , network topology , low voltage , voltage , graph theory , theoretical computer science , computer network , mathematics , engineering , electrical engineering , botany , combinatorics , biology
The correct topological relationship is crucial in the low‐voltage distribution network, as the actual topological structure of the low‐voltage distribution network changes frequently and tremendously due to the need of operation and maintenance, and it cannot be correctly reflected upon failure in timely updating of data, low circulation, poor quality etc. therefore, it is necessary to identify the topology. The knowledge graph technology can clearly reflect the existing relationship between data, deducing and mining hidden knowledge, suitable for topology identification of the low‐voltage distribution network. In the study, the knowledge graph technology was employed for topology identification: firstly, analyse the construction method of the knowledge graph, integrate data in multiple low‐voltage distribution network information systems based on the knowledge graph technology, deduce missing data, find out the relationship between data, and then build the knowledge graph of low‐voltage distribution network topological structure, and finally, based on ‘Typical Design Specification of Low‐Voltage Distribution Network Infrastructure Project’ and semantic segmentation, identify the user–transformer relationship in low‐voltage distribution network information system. The test results of the examples were very satisfactory, showing the theoretical values and practical application values of the identification method proposed in this study.