Energy Management for Renewable-Colocated Artificial Intelligence Data Centers

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.

Publication Details

Journal
ArXiv.org
Published
2025-07-04
Primary Topic
Cloud Computing and Resource Management
Type
article
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article

Energy Management for Renewable-Colocated Artificial Intelligence Data Centers

ArXiv.org
Cloud Computing and Resource Management
article

Energy Management for Renewable-Colocated Artificial Intelligence Data Centers

article en

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.

ArXiv.org
Affordable and clean energy
Openalex Percentile: Top 36%
Cloud Computing and Resource Management
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Energy Management for Renewable-Colocated Artificial Intelligence Data Centers · ArXiv.org (2025) | TGRS Research Map | TGRS