AI/ML data center growth have led to higher energy consumption and carbon emissions. The shift to renewable energy and growing data center energy demands can destabilize the power grid. Power grids rely on frequency regulation reserves, typically fossil-fueled power plants, to stabilize and balance the supply and demand of electricity. This paper sheds light on the hidden carbon emissions of frequency regulation service. Our work explores how modern GPU data centers can coordinate with power grids to reduce the need for fossil-fueled frequency regulation reserves. We first introduce a novel metric, Exogenous Carbon, to quantify grid-side carbon emission reductions resulting from data center participation in regulation service. We additionally introduce EcoCenter, a framework to maximize the amount of frequency regulation provision that GPU data centers can provide, and thus, reduce the amount of frequency regulation reserves necessary. We demonstrate that data center participation in frequency regulation can result in Exogenous carbon savings that oftentimes outweigh Operational carbon emissions.

翻译：人工智能/机器学习数据中心的增长导致了更高的能源消耗和碳排放。向可再生能源转型以及数据中心能源需求的增长可能使电网失稳。电网依赖频率调节储备（通常为化石燃料发电厂）来稳定和平衡电力供需。本文揭示了频率调节服务中隐藏的碳排放。我们的工作探讨了现代GPU数据中心如何与电网协调，以减少对化石燃料频率调节储备的需求。我们首先引入了一个新指标——外源性碳排放，以量化数据中心参与调节服务所带来的电网侧碳排放减少量。此外，我们提出了EcoCenter框架，旨在最大化GPU数据中心可提供的频率调节服务量，从而减少所需的频率调节储备量。我们证明，数据中心参与频率调节能够带来外源性碳减排，其效益通常超过数据中心自身的运行碳排放。