Multi source data security protection of smart grid based on edge computing

被引:0
|
作者
Xiao, Jianfei [1 ]
Wang, Yugang [1 ]
Zhang, Xiaolong [1 ]
Luo, Guijun [1 ]
Xu, Chuanyou [1 ]
机构
[1] Aostar Information Technologies Co.,Ltd., Sichuan, Chengdu,610000, China
来源
Measurement: Sensors | 2024年 / 35卷
关键词
Computing power - Data fusion - Data handling - Edge computing - Electric power supplies to apparatus - Electric power system protection - Electric power transmission - Electric power transmission networks - Maps - Outages - Risk assessment - Risk perception;
D O I
10.1016/j.measen.2024.101288
中图分类号
学科分类号
摘要
In order to cope with the continuous development of information technology, the data volume of edge devices in the power supply network is increasing rapidly, and the higher requirements for real-time data processing and transmission bandwidth are put forward, the author proposes the research on security protection of multi-source data in smart grid based on edge computing. Established a distribution network safety risk map, calculated and analyzed safety risks through potential functions, and obtained node potential values and key node data; The intelligent grid multi-source heterogeneous data monitoring model based on edge computing can realize the timely perception and real-time response of distribution network faults, shorten the outage time, and improve the power supply reliability and user satisfaction of the distribution network. The results indicate that: Taking a distribution network line in a certain area as an example, the highest potential value is node 9, followed by nodes 10 and 3. This indicates that in order to ensure the reliable operation of the distribution network and avoid power outages, it is necessary to improve the repair capacity, the proportion of old equipment, and the power supply radius exceeding the standard. Conclusion: The effectiveness of potential function in risk assessment of edge computing is verified, which can provide theoretical guidance for distribution network fault diagnosis. © 2024
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