A survey on the development status and application prospects of knowledge graph in smart grids
November 02, 2022 Β· The Cartographer Β· π IET Generation, Transmission & Distribution
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"Title-pattern auto-detect: A survey on the development status and application prospects of knowledge graph in smart grids"
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Authors
Jian Wang, Xi Wang, Chaoqun Ma, Lei Kou
arXiv ID
2211.00901
Category
cs.AI: Artificial Intelligence
Citations
96
Venue
IET Generation, Transmission & Distribution
Last Checked
1 day ago
Abstract
With the advent of the electric power big data era, semantic interoperability and interconnection of power data have received extensive attention. Knowledge graph technology is a new method describing the complex relationships between concepts and entities in the objective world, which is widely concerned because of its robust knowledge inference ability. Especially with the proliferation of measurement devices and exponential growth of electric power data empowers, electric power knowledge graph provides new opportunities to solve the contradictions between the massive power resources and the continuously increasing demands for intelligent applications. In an attempt to fulfil the potential of knowledge graph and deal with the various challenges faced, as well as to obtain insights to achieve business applications of smart grids, this work first presents a holistic study of knowledge-driven intelligent application integration. Specifically, a detailed overview of electric power knowledge mining is provided. Then, the overview of the knowledge graph in smart grids is introduced. Moreover, the architecture of the big knowledge graph platform for smart grids and critical technologies are described. Furthermore, this paper comprehensively elaborates on the application prospects leveraged by knowledge graph oriented to smart grids, power consumer service, decision-making in dispatching, and operation and maintenance of power equipment. Finally, issues and challenges are summarised.
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