Abstract
The core of digital twin is the digital reconstruction of physical space, that is the physical space perception and processed data are applied to the virtual space to achieve real-time map** of physical space through full integration of data. With the rapid development of digital twin technology in the power field, in order to achieve the purpose of real-time data fusion of physical space and virtual space in the digital twin of distribution network, the virtual and real data fusion processing technology for digital twin has become the focus of research in the power field. In this paper, firstly, the characteristics and ontology technology of power digital twin virtual and real data are studied, and an ontology-based virtual and real data fusion architecture is proposed. Then, a semantic feature extraction method is proposed for the structured and unstructured virtual and real data of power digital twin, and the extracted semantic features are formatted, described, and stored. Then the overall architecture of the distribution network digital twin virtual real data fusion system is designed, the technical route of the system is analyzed and discussed, and the virtual real data fusion processing is completed using the similarity algorithm and fusion rules based on the elements between ontology. Finally, the functional modules of the distribution network digital twin virtual real data fusion system are divided and introduced, and the digital twin virtual real data fusion of the fan hub casting process is verified as an example.
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Acknowledgements
This work was supported by State Grid Corporation of China’s Science and Technology Project (5108-202218280A-2-396-XG) which is 'Research on rapid construction and linkage analysis technology of distribution network facilities digital twins integrated with electrical topology'.
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Qiao, J. et al. (2024). Research and Implementation of Multi Fusion Data Model Construction Technology for Distribution Network Digital Twins. In: Kountchev, R., Patnaik, S., Wang, W., Kountcheva, R. (eds) Multidimensional Signals, Augmented Reality and Information Technologies. WCI3DT 2023. Smart Innovation, Systems and Technologies, vol 374. Springer, Singapore. https://doi.org/10.1007/978-981-99-7011-7_15
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DOI: https://doi.org/10.1007/978-981-99-7011-7_15
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