Research on Knowledge Graph Construction and Application for Online Emergency Load Transfer in Power Systems Article Swipe
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/electronics14173370
Efficient emergency load transfer is crucial for ensuring the power system’s safe operation and reliable power supply. However, traditional load transfer methods that rely on human experience have limitations, such as slow response times and low efficiency, which make it difficult to address complex and diverse fault scenarios effectively. Therefore, this paper proposes an emergency load transfer method based on knowledge graphs to achieve intelligent management and efficient retrieval of emergency knowledge. Firstly, a named entity recognition model based on ERNIE-BiGRU-CRF is constructed to automatically extract key entities and relationships from the load transfer plan texts, obtaining information such as fault names, fault causes, and operation steps. Secondly, a power system emergency load transfer knowledge graph is constructed based on the extracted structured knowledge, which is efficiently stored using a graph database and enables the visualization and interactive query of knowledge. Finally, real power system fault cases prove that the proposed method can effectively improve the retrieval efficiency of fault knowledge and provide intelligent support for online emergency load transfer decisions.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/electronics14173370
- https://www.mdpi.com/2079-9292/14/17/3370/pdf?version=1756119854
- OA Status
- gold
- References
- 12
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413670343
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4413670343Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/electronics14173370Digital Object Identifier
- Title
-
Research on Knowledge Graph Construction and Application for Online Emergency Load Transfer in Power SystemsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-08-25Full publication date if available
- Authors
-
Nan Lou, Shiqi Liu, Rong Yan, Ruiqi Si, Wanya Yu, Ke Wang, Zhantao Fan, Zhengbo Shan, Hongxuan Zhang, Xinyue Yu, Dawei Wang, Jun ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/electronics14173370Publisher landing page
- PDF URL
-
https://www.mdpi.com/2079-9292/14/17/3370/pdf?version=1756119854Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2079-9292/14/17/3370/pdf?version=1756119854Direct OA link when available
- Concepts
-
Knowledge transfer, Maximum power transfer theorem, Computer science, Graph, Knowledge graph, Distributed computing, Power (physics), Theoretical computer science, Knowledge management, Artificial intelligence, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
12Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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