Behind-the-Meter Energy Hub Dispatch for Data Centers

Mon, 01 Jan 0001 00:00:00 +0000

Problem

AI workloads can push a data center’s power demand up by tens of megawatts in minutes, often faster than its grid connection can supply. On-site gas turbines can cover the gap, but they respond over minutes while computing load changes in seconds. Keeping the two in balance without tripping any plant limit is a hard control problem.

Approach

Each side of the facility gets its own learned world model: one for the turbine fleet and one for the AI data hall. A single planner looks ahead across both at once and decides how far the turbines should ramp and how much work the data hall can safely defer. Every command is checked against the turbines’ physical limits before it reaches the plant, so the learned components never act unchecked.

Reinforcement-Learning on Omanshu Thapliyal

Behind-the-Meter Energy Hub Dispatch for Data Centers

Problem

Approach