A Q-learning based model-free wide-area damping control under GPS spoofing attacks

GPS欺骗攻击下基于Q学习的无模型广域阻尼控制

• 批准号: 560831-2020
• 负责人: Wang, Xiaozhe
• 金额: $ 2.19万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=707194
• 关键词: learning; based; model; free; wide

Ensuring the cybersecurity of modern electric power grids is critical to the social function and national security. The potential consequences of a successful large-scale cyberattack on a power grid cannot be overstated, since grid failures are not only costly but also profoundly disrupt people's daily lives and the delivery of essential services (water, food, health care, etc.). The proposed research project intends to study the impacts of one specific cyberattack, namely the global position system (GPS) spoofing attacks towards phasor measurement units (PMUs), on the wide-area damping control (WADC) of power systems and design a resilient WADC against the GPS spoofing attacks using machine learning techniques. The research outcomes will pave the way for enhancing the overall security and stability of Canadian power grids resilient to the GPS spoofing attacks. The results will also shed light on how we can defend against cyberattacks on electric power grids and minimize potential catastrophic consequences, ensuring the security and integrity of Canadian electric power grids.

确保现代电力电网的网络安全对于社会功能和国家安全至关重要。成功的大规模网络攻击在电网上的潜在后果不能被夸大，因为网格故障不仅是昂贵的，而且会严重破坏人们的日常生活和提供基本服务（水，食品，医疗保健等）的提供。拟议的研究项目旨在研究一个特定的网络攻击的影响，即全球位置系统（GPS）欺骗对相组测量单元（PMU）对电力系统的广泛区域阻尼控制（WADC）的攻击，并设计了使用机器学习技术的GPS欺骗攻击的弹性WADC。研究成果将为增强加拿大电力网的整体安全性和稳定性铺平道路，这对GPS欺骗攻击有弹性。结果还将阐明我们如何在电力网格上防御网络攻击，并最大程度地减少潜在的灾难性后果，从而确保加拿大电力电网的安全性和完整性。