In data centers, heating, ventilation, and air-conditioning (HVAC) consumes 30–40% of total energy consumption. Of that portion, 26% is attributed to fan power, the ventilation efficiency of which should thus be improved. As an alternative method for experimentations, computational fluid dynamics (CFD) is used. In this study, “parameter tuning”—which aims to improve the prediction accuracy of CFD simulation—is implemented by using the method known as “design of experiments”. Moreover, it is attempted to improve the thermal environment by using a CFD model after parameter tuning. As a result of the parameter tuning, the difference between the result of experimental-measurement results and simulation results for average inlet temperature of information-technology equipment (ITE) installed in the ventilation room of a test data center was within 0.2 °C at maximum. After tuning, the CFD model was used to verify the effect of advanced insulation such as raised-floor fixed panels and show the possibility of reducing fan power by 26% while keeping the recirculation ratio constant. Improving heat-insulation performance is a different approach from the conventional approach (namely, segregating cold/hot airflow) to improving ventilation efficiency, and it is a possible solution to deal with excessive heat generated in data centers.

Aiming to improve energy saving in regard to data centers, the authors have developed a high-efficiency air conditioner for use in data centers. In consideration of application to data centers, which are considered “mission-critical” facilities, development of air conditioners using a refrigerant — which have no effect on ICT equipment even in the event of leakage — has been continuing. A key feature of air conditioners for data centers is that they must provide sufficient cooling all year round, to handle the huge amount of heat generated by ICT equipment, and this is the key to energy saving. Given those circumstances, by improving compression efficiency in regard to outside environments in the low- to mid-temperature range and expanding the operational range at low pressure ratio, the authors developed a high-efficiency air conditioner [1]. Aiming to further reduce electrical power consumption, the authors developed an air conditioner whose pump cycle is juxtaposed on the conventional compression cycle. In more concrete terms, the pump cycle is configured so that low-temperature outside air (hereafter, “cold”) is imported into the refrigeration cycle via a heat exchanger (HEX) inside an outdoor unit. In the HEX, the cold is transferred to a refrigerant, which carries it into a computer room by means of a refrigerant pump. As one kind of indirect outside-air cooling method, this configuration does not degrade the quality of the air inside the computer room. Since the refrigerant pump (which consumes less power than the compressor) works when the outside air temperature is low, energy consumption is significantly reduced. In comparison with conventional air conditioners, the developed air conditioner can reduce annual power consumption by 54%, 50%, and 38% in the cases of Sapporo (Japan), New York (USA), and Austen (Texas, USA), respectively. We are sure that it will significantly contribute to reducing energy consumption of air conditioners used for data centers.

Energy-saving in regard to heating, ventilation, and air-conditioning (HVAC) in data centers is strongly required. Therefore, to improve the operating efficiency of the cooling equipment and extend the usage time of the economizer used for cooling information-technology equipment (ITE) in a data center, it is often the case that a high air-supply temperature within the range in which the ITE can be sufficiently cooled is selected. In the meantime, it is known that when the ambient temperature of the ITE rises, the speed of the built-in cooling fan increases. Acceleration of the built-in fan is thought to affect the cooling performance and energy consumption of the data center. Therefore, a method for predicting the temperature of a data center—which simply correlates supply-air temperature with ITE inlet temperature by utilizing existing indicators, such as air-segregation efficiency (ASE)—is proposed in this study. Moreover, a method for optimizing the total energy consumption of a data center is proposed. According to the prediction results obtained under the assumption of certain computer-room air-conditioning (CRAC) conditions, by lowering the ITE inlet temperature from 27 °C to 18 °C, the total energy consumption of the machine room is reduced by about 10%.