配电边缘物联网网络预警及自愈方案  

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

作　　者：李伟青 陈虹宇[2] 赵瑞锋 胡春强[2] LI Weiqing;CHEN Hongyu;ZHAO Ruifeng;HU Chunqiang(Meizhou Power Supply Bureau of Guangdong Power Grid Co.,Ltd.,Meizhou,Guangdong 514199,P.R.China;School of Big Data and Software Engineering,Chongqing University,Chongqing 401331,P.R.China;Electric Power Dispatching and Control Center,Guangdong Power Grid Company Ltd.,Guangzhou 510062,P.R.China)

机构地区：[1]广东电网有限责任公司梅州供电局,广东梅州514199 [2]重庆大学大数据与软件学院,重庆401331 [3]广东电网有限责任公司电力调度控制中心,广州510062

出　　处：《重庆大学学报》2023年第8期11-19,共9页Journal of Chongqing University

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

摘　　要：配电物联网是电力物联网建设中的最后一个环节,由于具有供电路径短、负荷密度大等特点,保护和控制的难度很大,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。为此,文中提出了适用于配电物联网边缘网络固件的安全防御技术框架,对存在边缘设备中的各固件可靠性矩阵进行保护,边缘设备通过边缘服务器相互连接,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。最后,通过不同环境下的模拟实验验证了文中方案的可行性。The distribution of IoT(Internet of Things)is the last link in the construction of ubiquitous power IoT.It possesses characteristics such as short power supply path and high load density,which bring about significant challenges in terms of protection and control.To address these challenges,the establishment of an early warning and self-healing strategy for the distribution network is crucial,enabling the formation of a smart distribution network with flexible operation mode,timely fault warning and perfect fault self-healing.This paper proposes a security defense technology framework applicable to the firmware of the distribution IoT edge network.The framework protects the reliability matrix of each firmware present in the edge devices,while the edge devices are interconnected through the edge servers,forming a technical solution for distribution edge IoT that incorporates security warning and self-healing capabilities.Finally,the feasibility of this scheme is verified by simulation experiments conducted under different environmental conditions.

关 键 词：人工智能 漏洞预警 配电物联网 电网自愈 

分 类 号：TM76[电气工程—电力系统及自动化] TM73