Current Projects
Characterizing Emerging Large Loads with LLM-Driven Models
Power Systems Engineering Research Center (PSERC), Award Number T-77
PI, with Co-PI Chee-Wooi Ten (Michigan Tech) and Co-PI Lang Tong (Cornell)
Awarded Amount: $185,000
Project Period: August 1, 2026 - July 31, 2028
Managing large electrical loads, such as data centers, industrial campuses, and high-performance computing facilities, is becoming a critical challenge for modern power systems, with direct implications for grid reliability, market operations, and renewable integration. These tens-to-hundreds-of-megawatt facilities exhibit highly dynamic, non-stationary demand patterns driven by computing workloads, cooling cycles, and operational policies. However, confidentiality, security concerns, and the absence of standardized data-sharing limit access to detailed measurements. To address this challenge, we will create a statistically and operationally realistic synthetic dataset to complement the limited real data available. Building on this foundation, the project will develop Large Language Model (LLM)-driven large load classification, disaggregation, and anomaly detection tools that work seamlessly with ISO, utility, and vendor analytics platforms. These capabilities will enable more accurate facility characterization, behind-the-meter analysis, and reliability assessment, preparing the T&D system for the next generation of high-impact loads.