<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

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

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

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...

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

Online veröffentlicht: 30. Nov. 2022

Seitenbereich: 591 - 600

Eingereicht: 07. Juli 2022

Akzeptiert: 16. Sept. 2022

DOI: https://doi.org/10.2478/amns.2021.2.00284

Schlüsselwörter
power system, Internet of things, power grid physical data, knowledge graph, deep learning

© 2023 Ting Hao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

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

Online veröffentlicht: 30. Nov. 2022

Seitenbereich: 591 - 600

Eingereicht: 07. Juli 2022

Akzeptiert: 16. Sept. 2022

DOI: https://doi.org/10.2478/amns.2021.2.00284

Schlüsselwörterpower system, Internet of things, power grid physical data, knowledge graph, deep learning

© 2023 Ting Hao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Schlüsselwörter
power system, Internet of things, power grid physical data, knowledge graph, deep learning