Evaporative cooling method to improve energy management of overhead downward flow-type data center

Abstract

The objective of this study was to improve the energy management of an overhead downward flow (ODF)-type data center (DC) using the evaporative cooling method. A computational fluid dynamics (CFD) approach was used to predict the optimal operating condition of an A1-grade DC exhibiting the smallest entropy generation rate of the ODF system. Experiments were performed to validate the predicted airflow speed at the inlet of each server and temperature distributions at the inlet and outlet of each server. Furthermore, three thermal performance metrics, namely rack cooling index (RCI), return temperature index (RTI), and supply heat index (SHI), were used to compare the numerical and experimental results, which were found to be consistent. The measured power usage effectiveness (PUE) reached 1.42, significantly lower than the global average PUE of 1.55 reported in 2022. Moreover, using the CFD method, water mist was added at the air supply port to reduce the temperature of air from 21.63 °C to 18 °C via evaporation and increase relative humidity from 50% to 70%. These results suggest that evaporative cooling has the potential to facilitate the supplied air to provide additional cooling capacity and lower the chiller load to reduce energy consumption in the DC.

Keywords

• Computational fluid dynamics (CFD)
• Data center (DC)
• Energy management
• Evaporative cooling
• Overhead downward flow (ODF)
• Thermal management