基于人工智能的配电边缘物联网网络预警及自愈方案
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作者单位:

1.广东电网有限责任公司梅州供电局;2.重庆大学大数据与软件学院;3.广东电网有限责任公司电力调度控制中心

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国家自然科学基金资助项目(62072065); 南方电网公司科技项目(031400KK52190059(GDKJXM20198151))。


Artificial intelligence-based early warning and self-healing technology for distribution edge IoT networks
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Affiliation:

1.Meizhou Power Supply Bureau of Guangdong Power Grid Co.,Ltd;2.School of Big Data and Software Engineering, Chongqing University, Chongqing,China;3.Electric Power Dispatching and Control Center, Guangdong Power Grid Company Ltd., Guangzhou China

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    摘要:

    配电物联网是泛在电力物联网建设中的最后一个环节,直接面向用户,是连接电力生产和用电用户的桥梁,影响着供电安全和供电可靠性的优劣。由于配电网具有供电路径短、负荷密度大等特点,导致保护和控制的难度很大,因此迫切需要建立完善的配电网预警和自愈策略,形成运行方式灵活、故障预警及时、故障自愈完善的智能配电网。本文提出适用于配电物联网边缘网络固件的安全防御技术框架,形成了具备安全预警及自愈能力的配电边缘物联网技术方案,并基于模拟实验验证了本方案的可行性。

    Abstract:

    The distribution IoT network is the last link in the construction of the ubiquitous power IoT, which directly faces the users and is the bridge connecting power production and electricity users, affecting the safety and reliability of power supply. Since the distribution network has the characteristics of short power supply path and high load density, which leads to great difficulties in protection and control, it is urgent to establish a perfect distribution network early warning and self-healing strategy to form a smart distribution network with flexible operation mode, timely fault warning and perfect fault self-healing. This paper proposed a security defense technology framework applicable to the distribution IoT edge network and terminals, forms a technical scheme of distribution edge IoT with security warning and self-healing capabilities, and verified the feasibility of this scheme based on simulation experiments.

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历史
  • 收稿日期:2021-11-15
  • 最后修改日期:2021-12-01
  • 录用日期:2021-12-02
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