In the drive to enhance data center energy efficiency, much attention has been placed on the prospect of airflow containment in hot-aisle cold-aisle raised floor arrangements. Such containment prevents airflow recirculation, eliminating the mixing effects of the hot and cold air streams that can cause an undesirable temperature rise at the inlet of the equipment racks. The intuitive assessment of the industry has been that the elimination of such mixing effects increases the energy efficiency of the data center cooling system by enabling delivery of air at higher inlet temperatures, thus reducing the amount of infrastructure cooling required. This paper employs an end-to-end modeling approach to analyze the effect of air stream containment in the computer room and its impact on the holistic system efficiency. Dimensionless heat index parameters are employed to characterize the effects of containment, recirculation, and mixing within the computer room environment. The extent of recirculation is shown to primarily influence the operation of the rack and computer room air conditioning (CRAC) level cooling systems, with the chiller systems also impacted. The overall effect on the complete cooling system performance and data center efficiency requires balancing of these effects. Through this model analysis, it is shown that containment may negatively impact overall energy efficiency in some circumstances, and that recirculation may actually be beneficial to overall energy efficiency under certain system dependent operating thresholds.
Cooperatively Improving Data Center Energy Efficiency Based on Multi-Agent Deep Reinforcement Learning
