将可再生能源与AI数据中心共址，优化调度降低用电成本。
Energy Management for Renewable-Colocated Artificial Intelligence Data Centers
- 共址系统协同调度AI任务、本地发电与电力市场交易。
- 实测数据表明用电成本显著下降，经济性提升明显。
- 适合关注绿色算力与能源协同的科研与工程人员。
我们为配备本地可再生能源的人工智能（AI）数据中心开发了一种能源管理系统（EMS）。在成本最小化框架下，该共址数据中心（RCDC）的EMS协同优化AI工作负载调度、本地可再生能源利用及电力市场参与。无论在批发还是零售市场模式下，均能最大化运营经济效益。基于真实电价、数据中心功耗和可再生能源生成数据的实证评估显示，可再生能源与AI数据中心共址可带来显著的电费节省。
原文摘要 · Abstract (English)
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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