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基于“云管边端”技术的设备风险防范研究
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Abstract:
在电力台区设备接入用户数逐步增加以及电力设备风险防范越来越重要的背景下,对台区设备进行风险防范的必要性逐渐显现,目前虽然设备的风险防范已有一定的研究及实践,然而在实践过程中,对于电力领域设备数量多、范围广、数据复杂的情况仍没有高效的解决方案。本文提出一种基于“云管边端”技术的台区设备进行风险防范方法,基于本文所述方法,能够显著提高风险防范的效率以及准确性。
In the context of the gradual increase in the number of users connected to power distribution station and the increasing importance of power equipment risk prevention, the necessity of risk prevention for power distribution station has gradually emerged. Although there has been certain research and practice on equipment risk prevention, however, in the process of practice, there is still no efficient solution for the large number of equipment, wide range, and complex data in the power field. This paper proposes a risk prevention method for power distribution station based on the “cloud-network-edge-end” technology. Based on the method described in this article, the efficiency and accuracy of risk prevention can be significantly improved.
[1] | 陆冰芳, 张希翔. 基于机器学习的电网信息系统安全风险预测模型构建[J]. 电子设计工程, 2020, 28(13): 128-132. |
[2] | 熊小敏, 杨鑫, 刘兆璘, 朱雪田. 车路协同的云管边端架构及服务研究[J]. 电子技术应用, 2019, 45(8): 14-18+31. |
[3] | 徐亚兰, 郭承军. 基于边缘计算的高精度地图数据处理方法研究现状[C]//第十一届中国卫星导航年会. 论文集S02导航与位置服务, 2020: 96-101. |