A hierarchical request-acceptance protocol with learning-based planning and robust TSO evaluation reduces curtailment for GW-scale AI data centers from 9.1% to 2.8% while preserving 98.1% of frontier training workload.
Internet data centers participating in electricity network transition considering carbon -oriented demand response
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Grid Integration of Gigawatt-Scale AI Data Centers under Connect-and-Manage
A hierarchical request-acceptance protocol with learning-based planning and robust TSO evaluation reduces curtailment for GW-scale AI data centers from 9.1% to 2.8% while preserving 98.1% of frontier training workload.