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Voltage Regulation in Distribution Systems with Data Center Loads
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Recent boom in foundation models and AI computing have raised growing concerns on the power and energy trajectories of large-scale data centers. This paper focuses on the voltage issues caused by volatile and intensity of data center power demand, which also aligns with recent observations of more frequent voltage disturbances in power grids. To address these data center integration challenges, we propose a dynamic voltage control scheme by harnessing data center's load regulation capabilities. By taking local voltage measurements and adjusting power injections at each data center buses through the dynamic voltage and frequency scaling (DVFS) scheme, we are able to maintain safe voltage magnitude in a distributed fashion with higher data center computing load. Simulations using real large language model (LLM) inference load validate the effectiveness of our proposed mechanism. Both the LLM power data and proposed control scheme are open sourced.
Forward citations
Cited by 2 Pith papers
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OpenG2G: A Simulation Platform for AI Datacenter-Grid Runtime Coordination
OpenG2G is a new extensible simulation platform that lets users implement and compare classic, optimization, and learning-based controllers for AI datacenter power flexibility coordinated with the grid.
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GPU-to-Grid: Voltage Regulation via GPU Utilization Control
GPU batch-size control, driven by real-time voltage and latency feedback, can serve as a fast distribution-grid voltage regulation resource.
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