False data injection attacks targeting power system generation control/scheduling and their mitigations

电力系统容易受到网络攻击。在这个项目中，我们打算研究针对电力系统自动发电控制(AGC)和经济调度(ED)的虚假数据注入攻击(FDIA)。此类攻击可能会严重影响系统的频率稳定性，造成巨大的经济损失甚至灾难性的停电。特别是，我们将从入侵者的角度开发针对AGC和ED的新型FDIA模型，评估所开发的FDIA对基准测试系统的影响，然后从防御者的角度设计针对这些FDIA的有效缓解方法，以减少FDIA的负面影响，确保电网的安全运行。研究结果将阐明我们如何更好地保卫加拿大的电网，并最大限度地减少对该国关键基础设施的安全和完整性的灾难性后果，以抵御日益频繁和严重的潜在网络攻击。

Electric power systems are subject to cyberattacks. In this project, we intend to investigate false data injection attacks (FDIAs) targeting the automatic generation control (AGC) and the economic dispatch (ED) of electric power systems. Such a class of attacks may significantly affect the system frequency stability and result in huge economic loss and even catastrophic blackouts. Particularly, we will develop novel FDIA models targeting AGC and ED from the intruder's perspectives, evaluate the impacts of developed FDIAs on benchmark test systems, and then design effective mitigation methods against those FDIAs from the defender's viewpoint to reduce the negative impacts of the FDIAs and ensure the secure operation of power grids. The research outcomes will shed light on how we can better defend Canada's power grids and minimize catastrophic consequences on the security and integrity of the country's critical infrastructures against potential cyberattacks that are increasing both in frequency and severity.