ERI: Reaction Mechanisms Against Cyberattacks Designed to Result in Voltage Collapse in Smart Power Distribution Systems: Modeling and Experimental Validation Frameworks

ERI：针对旨在导致智能配电系统电压崩溃的网络攻击的反应机制：建模和实验验证框架

• 批准号: 2348420
• 负责人: Arash Asrari
• 金额: $ 19.95万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2348420&HistoricalAwards=false
• 关键词: ERI; Reaction; Mechanisms; Against; Cyberattacks

Despite high levels of security redundancy in the U.S. bulk electric power grid, it is acknowledged that a sophisticated cyber attack could potentially bring down the U.S. power system. Strengthening the cyber security of national infrastructures such as the power grid is of major concern. This has led to a significant research literature on power systems cybersecurity. Most of this literature focuses on cyberattack prevention and less on dealing with attacks aimed at bypassing the detection stage. Hence, this research will study reaction mechanisms to remediate incidents on power systems that are caused by cyberattacks bypassing the detection stage. The developed remedial action frameworks in this project will yield new insights that will be valuable to researchers/engineers working on resilience improvement for smart distribution systems against non-detectable cyberattacks. The outcomes of this research will be shared with professional engineers (PEs) via industry seminars, providing professional development hours and updating their knowledge on vulnerability of power systems to cyberattacks. In addition, the project will broaden participation in engineering through summer workshops to involve K-12 students from underrepresented groups for the purpose of diversifying the STEM leaders for modern operation of the U.S power grid.The focus of this project is to address the following research issue: “How to react to cyberattacks on the load tap changing (LTC) mechanism of autotransformers within power distribution systems to tackle an intended voltage collapse.” Within this scope, the first objective of the research is to investigate vulnerability of LTCs to cyberattacks targeting voltage collapse in distribution systems. Reaching this objective for a distribution system operator will result in a sophisticated attack model that bypasses state estimation-based bad data detection, based on which realistic remedial actions can be developed. The second objective is to design primary/backup reaction mechanisms to mitigate the voltage collapse resulting from the attacked LTCs. To attain this objective, several algorithms will be created to design a primary remediation technique based on distribution network reconfiguration customized by a deep learning framework. The primary reaction scheme will be supported by a backup electricity market-based mechanism, where distributed synchronous generators will optimally contribute to mitigation of cyberattacks in the regions of the system not fully alleviated by network reconfiguration. Finally, the third objective of this research is to perform hardware-in-the-loop experimental validation of the proposed remedial actions on a lab-scale smart microgrid.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

尽管美国批量电力电网的安全冗余水平很高，但人们承认，复杂的网络攻击可能会降低美国电力系统。加强国家基础设施（例如电网）的网络安全是主要的关注。这导致了有关电力系统网络安全的重要研究文献。这些文献的大多数都集中在预防网络攻击上，而少于处理旨在绕过检测阶段的攻击。因此，这项研究将研究反应机制，以补救由绕过检测阶段的网络攻击引起的电力系统事件。该项目中开发的补救行动框架将产生新的见解，这对于针对不可检测的网络攻击的智能分配系统的研究人员/工程师来说将很有价值。这项研究的结果将通过行业半手与专业工程师（PES）共享，提供专业开发时间并更新他们对电力系统脆弱性网络攻击的知识。 In addition, the project will broaden participation in engineering through summer workshops to involve K-12 students from underrepresented groups for the purpose of diversifying the STEM leaders for modern operation of the U.S power grid.The focus of this project is to address the following research issue: “How to react to cyberattacks on the load tap changing (LTC) mechanism of autotransformers within power distribution systems to tackle an intended voltage collapse."在此范围内，该研究的第一个目标是研究LTC对针对分配系统电压崩溃的网络攻击的脆弱性。达到分配系统操作员的目标将导致一个复杂的攻击模型，该模型绕过基于状态估计的不良数据检测，基于该模型，可以根据该模型开发现实的补救措施。第二个目标是设计主要/备份反应机制，以减轻受攻击的LTC导致的电压塌陷。为了攻击这一目标，将创建几种算法来设计基于通过深度学习框架定制的分布网络重新配置的主要补救技术。主要反应方案将得到备用电力市场的机制支持，在该机制中，分布式同步发电机将最佳地减轻无法完全缓解网络重新配置的系统区域的网络攻击。最后，这项研究的第三个目标是对实验室规模的智能微电网对拟议的补救措施进行硬件实验验证。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准来评估来获得的支持。