Energy Management for Renewable-Colocated Artificial Intelligence Data Centers

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Authors: Siying Li, Lang Tong, T. D. Mount
Cited by: 2
References: 5

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.

Fields of Study & Subjects

Cloud Computing and Resource Management Green IT and Sustainability Big Data and Digital Economy

Publication details

Journal / source
2026 IEEE PES International Meeting (PES IM)
Publisher
IEEE
Pages
1–5
Publication date
18 January 2026