Paper
16 December 2022 Design and implementation of a multi-source data fusion scheme based on configuration software for smart energy
Yu Meng, Ying Wang, Zesan Liu, Xiaozhen Li, Tingting Yan
Author Affiliations +
Proceedings Volume 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022); 125001W (2022) https://doi.org/10.1117/12.2661022
Event: 5th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022, Chongqing, China
Abstract
With the rapid development of new power systems and smart energy, data sources for energy equipment are being greatly expanded, and integrated power scenarios are becoming more sophisticated and complex. As a visualization tool that can quickly build smart energy scenarios, configuration software has been unable to efficiently respond to the increasing number of cross-system and multi-granularity display requirements. In order to address the serious shortcomings of configuration software in data display, this paper proposes a new multi-source data fusion scheme that achieves the linkage effect between equipment model attributes and multi-source binding data via flexible and configurable multi-source data selection components and dynamically assigned functions. At the same time, the hybrid communication mechanism is used to optimize the data refresh performance, and finally, multi-source data fusion of a single model is realized, which improves energy visualization accuracy. In the end, an example scenario is compared to the existing solution to validate the paper's proposed scheme's simplicity, flexibility, and agility.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yu Meng, Ying Wang, Zesan Liu, Xiaozhen Li, and Tingting Yan "Design and implementation of a multi-source data fusion scheme based on configuration software for smart energy", Proc. SPIE 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 125001W (16 December 2022); https://doi.org/10.1117/12.2661022
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KEYWORDS
Data modeling

Fusion energy

Data fusion

Visualization

Data communications

Visual process modeling

Software development

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