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arXiv · 2507.08011

Energy Management for Renewable-Colocated Artificial Intelligence Data Centers

Siying Li·Lang Tong·Timothy D. Mount
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Abstract

We develop an energy management system (EMS) for artificial intelligence (AI) data centers with colocated renewable generation. Under a cost-minimizing framework, the EMS of renewable-colocated data center (RCDC) co-optimizes AI workload scheduling, on-site renewable utilization, and electricity market participation. Within both wholesale and retail market participation models, the economic benefit of the RCDC operation is maximized. Empirical evaluations using real-world traces of electricity prices, data center power consumption, and renewable generation demonstrate significant electricity cost reduction from renewable and AI data center colocations.

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Siying Li, Lang Tong, Timothy D. Mount. 2025-07-04. Energy Management for Renewable-Colocated Artificial Intelligence Data Centers. https://arxiv.org/abs/2507.08011

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