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Construction and intelligent analysis of power grid physical data knowledge graph based on Internet of Things for power system

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The State Grid Corporation of China proposed the idea of building a ubiquitous power Internet of Things, which intends to endow the power system with adjustable perceptivity through the Internet of Things technology. Aiming at the power system under the Internet of Things, this article propounds a framework for the construction and intelligent assessment of the knowledge graph (KG). First of all, the introduction of the power Internet of Things system architecture and data life cycle will be introduced from the aspects of organisational structure, management system, team building, technical support and data security protection. Then, the key information is mined from the complicated physical text data of the power grid by using NLP technology. At the same time, a hybrid model is propounded for named entity recognition, which effectively uses context information to meliorate the accuracy of extraction. The experimental results evince that the accuracy rate of the Internet-based grid physical data KG construction and intelligent analysis framework proposed in article reaches 96.53%. It is a new guidance for the research and evolution of future power grid objects.

eISSN:
2444-8656
Langue:
Anglais
Périodicité:
1 fois par an
Sujets de la revue:
Sciences de la vie, autres, Mathématiques, Mathématiques appliquées, Mathématiques générales, Physique