PI: Long Vu, Energy and Environment Directorate 

LLM4RL addresses the simulation2reality gap in grid control by leveraging the power of LLMs and the expertise of power engineers to generate a small, physics-grounded set of grid models for reinforcement learning (RL) training, for which the robustness of RL control is achievable on both simulated and deployed power grids.