NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
NSF
The U.S. energy sector has experienced a sharp rise in cyberattacks, particularly targeting electricity market participants at the distribution level. These participants—such as retailers representing distributed energy resources (DERs) and smart homes—are essential to modern electricity markets but also introduce new vulnerabilities. Among the most dangerous threats are coordinated false data injection (FDI) attacks that manipulate market data to disrupt power dispatch, pricing, and system configurations. These attacks can result in power outages, inflated prices, voltage instability, and grid congestion. Despite advancements in cybersecurity research, there is currently no cohesive solution for both detecting and remediating such coordinated cyberattacks on distribution-level market retailers. This project addresses that critical gap, which aligns with the NSF’s mission to advance the energy infrastructure by integrating innovative technologies and solutions to ensure reliability and robustness of power systems against emerging threats. It also contributes to the emerging field of smart grid cybersecurity, with a special focus on market-based operations. The intellectual merit of this proposed project includes the design of a cohesive protection framework that combines detection and proactive mitigation to minimize the impact of coordinated FDI cyberattacks, alongside post-attack remediation to fully resolve operational issues caused by these attacks on DER retailers and smart home retailers in deregulated electricity markets. The broader impacts of this proposed project include the integration of research findings into new educational materials and curriculum on electricity markets and cybersecurity, hands-on research opportunities for graduate and undergraduate students, high school summer engineering workshops open to all interested participants, and industry seminars for professional engineers. These activities aim to enhance STEM education and support workforce development in the energy and cybersecurity sectors. This project will achieve three technical objectives: First, it will identify the effectiveness of generalized coordinated cyberattacks on market retailers of distribution systems. Second, it will develop a quantum-secure federated detection system, enabling private, collaborative model training across retailers of smart homes and DERs to flag anomalous patterns in bids and sensor data. Third, it will implement a two-tier operational response: (i) a collaborative coordination strategy among trusted market retailers using anomaly-informed adjustments, and (ii) a dynamic control zone segmentation approach to stabilize system operation. The research will combine optimization techniques, secure machine learning, and hardware-in-the-loop experimental validation using a lab-scale smart microgrid. Together, these methods aim to reduce the operational and economic impacts of cyberattacks on electricity market retailers while strengthening grid security. 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.
Up to $299K
2028-08-31
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.
One-time $749 fee · Includes AI drafting + templates + PDF export
Research Infrastructure: National Geophysical Facility (NGF): Advancing Earth Science Capabilities through Innovation - EAR Scope
NSF — up to $26.6M
AmLight: The Next Frontier Towards Discovery in the Americas and Africa
NSF — up to $9M
CREST Phase II Center for Complex Materials Design
NSF — up to $7.5M
EPSCoR CREST Phase I: Center for Energy Technologies
NSF — up to $7.5M
EPSCoR CREST Phase I: Center for Post-Transcriptional Regulation
NSF — up to $7.5M
EPSCoR CREST Phase I: Center for Semiconductors Research
NSF — up to $7.5M