Research, development and demonstration of a natural hazard and large language model enhanced electric grid planning tool the overall objective of this project is to help improve the resilience of the…

Texas A&M Engineering Experiment Station received a $3.49 million Cooperative Agreement from the Department of Energy's Office of Cybersecurity, Energy Security, and Emergency Response (CESER) under the Cybersecurity, Energy Security & Emergency Response program (CFDA 81.008), effective October 1, 2025, through September 30, 2028. The award funds research, development, and demonstration of an integrated planning tool that combines natural hazard analysis with large language model (LLM) capabilities to enhance electric grid resilience and long-term infrastructure planning. This three-year project directly supports CESER's Risk Management Tools and Technologies division objective to develop next-generation tools addressing risks to U.S. energy infrastructure from natural hazards, extreme weather, and climate change impacts.

The primary deliverable is an advanced decision-support tool designed to assist stakeholders responsible for long-term electric grid investment decisions by providing improved analytical capabilities for planning grid infrastructure under uncertain future conditions. By leveraging both natural hazard modeling and artificial intelligence technologies, the tool will enable more informed grid resilience planning and operational decision-making. Work will be performed at Texas A&M's College Station, Texas facility, with the institution drawing on its established expertise in advanced engineering research, energy technologies, and complex system analysis to develop and demonstrate this capability for the energy sector.

Research, development and demonstration of a natural hazard and large language model enhanced electric grid planning tool the overall objective of this project is to help improve the resilience of the US electric grid to deal with natural hazards, such as those due to climate change and extreme weather. Specifically, the objective is to provide improved tools to help the people making long-term investment decisions better plan the grid for what will surely be an uncertain future.