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

Q4 Engineering
Jianfei Xiao, Yugang Wang, Xiaolong Zhang, Guijun Luo, Chuanyou Xu
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引用次数: 0

Abstract

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.

基于边缘计算的智能电网多源数据安全保护
为应对信息技术的不断发展,电网边缘设备数据量快速增长,对数据实时处理和传输带宽提出了更高的要求,笔者提出了基于边缘计算的智能电网多源数据安全防护研究。建立了配电网安全风险图谱,通过势函数计算分析安全风险,得到节点势值和关键节点数据;基于边缘计算的智能电网多源异构数据监测模型,可实现配电网故障的及时感知和实时响应,缩短停电时间,提高配电网供电可靠性和用户满意度。研究结果表明以某地区配电网线路为例,节点 9 的电位值最高,其次是节点 10 和节点 3。这说明为了保证配网的可靠运行,避免停电事故的发生,必须提高抢修能力、老旧设备比例、超标供电半径等。结论验证了势函数在边缘计算风险评估中的有效性,可为配网故障诊断提供理论指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Measurement Sensors
Measurement Sensors Engineering-Industrial and Manufacturing Engineering
CiteScore
3.10
自引率
0.00%
发文量
184
审稿时长
56 days
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