坏数据对基于PMU的线路故障检测的影响
Impacts of Bad Data on the PMU based Line Outage Detection
AI总结：
本文研究了通过注入虚假数据掩盖线路故障的方法，利用KCL和KVL保证数据不被检测，同时通过优化攻击向量增大残差以避免PMU检测到故障。
摘要：
由于信息技术的高集成度，电力系统更容易受到网络攻击。本文证明通过向测量数据中注入虚假数据可以掩盖部分线路故障。攻击成功的关键在于：1) 注入的虚假数据符合KCL和KVL，以避免被状态估计中的坏数据检测程序发现；2) 增大残差使得PMU数据无法检测到线路故障。通过建立二次规划问题确定最优攻击向量以最大化故障线路的残差。IEEE 39节点系统用于验证该掩盖方案。
英文摘要：
Power systems become more prone to cyber-attacks due to the high integration of information technologies. In this paper, we demonstrate that the outages of some lines can be masked by injecting false data into a set of measurements. The success of the topology attack can be guaranteed by making that: 1)the injected false data obeys KCL and KVL to avoid being detected by the bad data detection program in the state estimation; 2)the residual is increased such that the line outage cannot be detected by PMU data. A quadratic programming problem is set up to determine the optimal attack vector that can maximize the residual of the outaged line. The IEEE 39-bus system is used to demonstrate the masking scheme.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
