Wedan Emmanuel Gnibga, Andrew A. Chien, Anne Blavette, Anne Cécile Orgerie
In an era of growing water demand and amplifying climatic disruptions, water is an increasingly limited and precious resource. As datacenters continue to proliferate due in particular to growing artificial intelligence demand, datacenter reliance on water for cooling is drawing increasing criticism.
In this paper, we investigate the water and energy consumption, carbon emissions, and cost associated with the energy demand (including its cooling) from a datacenter, in four diverse locations (California, Texas, Germany, and France). We consider water use both in evaporative cooling and power generation, employing a hybrid datacenter cooling model that is operable with and without evaporative cooling. Subsequently, we examine solutions that expand the equipment’s operational range and actively exploit the cooling design redundancy. Moreover, we investigate the benefits of making datacenters dynamic, that is changing operating balance hourly. The results show that using dry cooling in California reduces the water average consumption by 4.34 million of gallon per month with minimal increase in TCO (0.7%). However in France, water saving increases TCO by up to 3.9x more than in California. The story for carbon emissions is more complicated, dry cooling increases total carbon emissions in some geographies (California, Texas), but has minimal impact in others (France).
Operating cooling equipment more aggressively enables wider datacenter operation ranges and the reduction of carbon emissions by 1.36%. This approach also improves the PUE of dry cooling and can produce lower TCO in the future.