An increased energy demand, and environmental pressure to accommodate higher levels of renewable energy and flexible loads like electric vehicles have led to numerous smart transformations in the modern power systems. These transformations make the cyber-physical power system highly susceptible to cyber-adversaries targeting its numerous operations. In this work, a novel black box adversarial attack strategy is proposed targeting the AC state estimation operation of an unknown power system using historical data. Specifically, false data is injected into the measurements obtained from a small subset of the power system components which leads to significant deviations in the state estimates. Experiments carried out on the IEEE 39 bus and 118 bus test systems make it evident that the proposed strategy, called DeeBBAA, can evade numerous conventional and state-of-the-art attack detection mechanisms with very high probability.
翻译:能源需求增加,环境压力增加,以适应可再生能源和电动车辆等弹性载荷的较高水平,导致现代电力系统出现许多智能转型。这些转型使网络物理动力系统极易成为针对其众多行动的网络反向系统。在这项工作中,提议采用新的黑盒对抗攻击战略,针对AC国家利用历史数据对未知电力系统进行估算。具体地说,错误数据被注入从电力系统部件的一小部分获得的测量数据中,这导致国家估计出现重大偏差。在IEEEE 39大客车和118大客车测试系统上进行的实验表明,拟议的战略叫做DeeBBAA, 能够非常可能地避开许多常规和最先进的攻击探测机制。</s>