论文标题
虚假数据注射对电动汽车辅助电压法规的攻击
False Data Injection Attack on Electric Vehicle-Assisted Voltage Regulation
论文作者
论文摘要
随着电动汽车（EV）的大规模渗透和双向充电器的出现，EV聚合器将成为电压调节市场的主要参与者。本文提出了针对电压充电站的电压调节容量估计的新型虚假数据注射攻击（FDIA），这是分配系统中电压调节的过程。拟议的FDIA考虑了EV移动性和网络条件的不确定性。预期不利影响最大的攻击向量是解决随机优化问题的解决方案，但要确保其可以绕过不良数据检测的约束。我们表明，可以通过求解一系列凸面四边形线性程序来确定此攻击向量。基于两个标准测试馈线的共模拟平台中检查的案例研究揭示了电压调节容量估计的脆弱性。
With the large scale penetration of electric vehicles (EVs) and the advent of bidirectional chargers, EV aggregators will become a major player in the voltage regulation market. This paper proposes a novel false data injection attack (FDIA) against the voltage regulation capacity estimation of EV charging stations, the process that underpins voltage regulation in distribution system. The proposed FDIA takes into account the uncertainty in EV mobility and network conditions. The attack vector with the largest expected adverse impact is the solution of a stochastic optimization problem subject to a constraint that ensures it can bypass bad data detection. We show that this attack vector can be determined by solving a sequence of convex quadratically constrained linear programs. The case studies examined in a co-simulation platform, based on two standard test feeders, reveal the vulnerability of the voltage regulation capacity estimation.
