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The thermal management and reduction of energy consumption in cooling systems have become major trends with the continued growth of high heat dissipation data centers and the challenging energy situation. However, the existing studies have been limited to studying the influences of individual factors on energy saving and thermal management and have not been systematically summarized. Thus, this paper reviews the key factors in achieving thermal management and reducing energy consumption in each cooling system, the corresponding research, and optimization methods. To achieve these goals, in this paper, literature surveys on data center cooling systems are investigated. For data center air cooling, thermal management is mainly related to the uniform distribution of hot and cold air. Adjusting the porosity of perforated tiles can reduce energy consumption. For liquid cooling and free cooling systems, climate conditions, cooling system structural design, coolant type, and flow rate are key factors in achieving thermal management and reducing energy consumption. This paper provides the power usage effectiveness (PUE) values of the cooling systems in some cases. A summary of the key factors can provide directions for research on thermal management and energy reduction, and a summary of previous research can provide a basis for future optimization. [ABSTRACT FROM AUTHOR]

A novel energy-saving hybrid cooling system that combines a forced-cooling cycle and a free-cooling cycle was developed to increase the energy efficiency of cooling systems in year-round operation of an internet data center with high heat loads. This system effectively utilizes a dam deep water source to reduce energy consumption in internet data centers. The hybrid cooling system operates in forced-cooling mode when the entering water temperature exceeds the mode change temperature of 9 °C, but switches to free-cooling mode when the ambient temperature falls below the mode change temperature. In this paper, the cooling performance of the hybrid system was assessed under various operating conditions based on entering water temperature fluctuation. Because the cooling effectiveness of this type of system is highly dependent on the outside climate, its usefulness and suitability for different periods and zones must be investigated. The annual energy saving performance of the new system was estimated and compared to a conventional cooling system in terms of the integrated coefficient of performance, based on the hourly weather air temperature and water temperature bin data collected from 16 cities of different climate zones in South Korea. The experimental findings revealed that the novel hybrid internet data center cooling system showed a 67% annual operating performance over a conventional air source internet data center cooling system due to the adoption of a dam deep water source. [ABSTRACT FROM AUTHOR]

In the age of the digital economy, the data center is the most crucial piece of infrastructure. The issue of the excessive power consumption of a data center's cooling system needs to be addressed as the national objective of "peak carbon and carbon neutrality" is increasingly promoted. In this study, a microchannel-separated heat pipe-cooling system with evaporative condensation is introduced. The system may switch between three modes of operation in response to changes in outdoor air quality parameters, thereby maximizing the utilization of natural cooling sources while lowering data centers' cooling costs. The purpose of this paper is to analyze the energy-saving potential of the hybrid system through experimental tests. The results show that 114.4% is the ideal liquid-loading rate for the heat pipe system. Under working conditions in Xi'an, the annual operating hours of the three modes accounted for 47.2%, 6.1%, and 46.7%. The hybrid cooling system may save 62.04% of the energy used annually compared to the standard cooling system and the cooling system in the server room thanks to its yearly average COP of 9.43. [ABSTRACT FROM AUTHOR]

As one of the most promising thermal management solutions, spray cooling has the advantages of high heat-transfer coefficient and maintaining a low temperature of the cooling surface. By summarizing the influential factors and practical applications of spray cooling, the current challenges and bottlenecks were indicated so as to prompt its potential applications in the future. Firstly, this paper reviewed the heat-transfer mechanism of spray cooling and found that spray cooling is more advantageous for heat dissipation in high-power electronic devices by comparing it with other cooling techniques. Secondly, the latest experimental studies on spray cooling were reviewed in detail, especially the effects of spray parameters, types of working fluid, surface modification, and environmental parameters on the performance of cooling system. Afterwards, the configuration and design of the spray cooling system, as well as its applications in the actual industry (data centers, hybrid electric vehicles, and so on) were enumerated and summarized. Finally, the scientific challenges and technical bottlenecks encountered in the theoretical research and industrial application of spray cooling technology were discussed, and the direction of future efforts were reasonably speculated. [ABSTRACT FROM AUTHOR]

Commercial solutions in the area of data center cooling available on the market are universal solutions that use dedicated control methods and are to able function properly in a wide range of working conditions. The functional limitations resulting in their application were our motivation for developing our own system architecture and a dedicated control algorithm. Historical data from an operating cooling system were analyzed. On that basis, a rule-based controller was developed, the purpose of which is to correctly switch between operating modes. The time constants of the automation actuators and the dynamics of the changes that occur in the cooling process were identified. The control strategy was experimentally validated throughout 2017. The efficacy of the second solution and the effectiveness of the control algorithm throughout the calendar year were demonstrated. Our solution allows individual control of each element of the cooling system. This enabled the extension of the operation time in the free-cooling mode by 2064 h throughout the year, a 69% increase in the COP coefficient of the cooling system and a reduction in electricity consumption by 206.9 MWh due to longer operation in the freecooling mode. [ABSTRACT FROM AUTHOR]

Improving the energy efficiency of data center has become a research focus in recent years. Previous works commonly adopted the inlet temperature constraint to optimize the thermal environment in the data center. However, the inlet temperature-aware method cannot prevent the servers from over-cooling. To cope with this issue, we propose a thermal-aware workload allocation strategy with respect to the chip temperature constraint. In this paper, we conducted a comparative evaluation of the performance between the chip and inlet temperature-aware workload allocation strategies. The workload allocation strategies adopt a POD-based heat recirculation model to characterize the thermal environment in data center. The contribution of the temperature-dependent leakage power to server power consumption is also considered. We adopted a sample data center under constant-flow and variable-flow cooling air supply to evaluate the performance of these two different workload allocation strategies. The comparison results show that the chip temperature-aware workload allocation strategy prevents the servers from over-cooling and significantly improves the energy efficiency of data center, especially for the case of variable-flow cooling air supply. [ABSTRACT FROM AUTHOR]

The worldwide demand on data storage continues to increase and both the number and the size of data centers are expanding rapidly. Energy efficiency is an important factor to consider in data centers since the total energy consumption is huge. The servers must be cooled and the performance of the cooling system depends on the flow field of the air. Computational Fluid Dynamics (CFD) can provide detailed information about the airflow in both existing data centers and proposed data center configurations before they are built. However, the simulations must be carried out with quality and trust. The k--ε model is the most common choice to model the turbulent airflow in data centers. The aim of this study is to examine the performance of more advanced turbulence models, not previously investigated for CFD modeling of data centers. The considered turbulence models are the k--ε model, the Reynolds Stress Model (RSM) and Detached Eddy Simulations (DES). The commercial code ANSYS CFX 16.0 is used to perform the simulations and experimental values are used for validation. It is clarified that the flow field for the different turbulence models deviate at locations that are not in the close proximity of the main components in the data center. The k--ε model fails to predict low velocity regions. RSM and DES produce very similar results and, based on the solution times, it is recommended to use RSM to model the turbulent airflow data centers. [ABSTRACT FROM AUTHOR]

Demand is soaring for data centers with advanced data-processing capabilities. In data centers with high-temperature information technology (IT) equipment, enormous cooling systems are operated year-round. To date, studies have aimed to improve the cooling efficiency of server-room units, but cooling-energy-consumption analysis considering the recirculation of exhaust air (EA) has not been researched to a sufficient degree. This study analyzed the cooling-energy saving effects considering the EA-recirculation and supply-air (SA)-temperature conditions when direct and indirect air-side economizers were applied to a data center in Korea. Thirteen case studies were conducted. The results showed that when the EA-recirculation ratio in the direct air-side economizer was 15%, its annual cooling-energy consumption increased by approximately 6.1% compared to the case with no recirculation. The indirect air-side economizer also exhibited an approximately 9% increase in cooling-energy consumption. On the other hand, when the SA temperature changed to 22 °C, the annual cooling-energy consumption of the direct and indirect air-side economizers decreased by approximately 67% and 55%, respectively, compared to a central chilled-water system. This indicates the importance of developing measures to prevent EA recirculation and of securing a wind path for the improvement of air-conditioning efficiency in data centers at the design stage. [ABSTRACT FROM AUTHOR]

Information technology (IT) has brought significant changes in people's lives. As an important part of the IT industry, data centres (DCs) have been rapidly growing in both the number and size over the past 40 years. Around 30% to 40% of electricity consumption in DCs is used for space cooling, thus leading to very inefficient DC operation. To identify ways to reduce the energy consumption for space cooling and increase the energy efficiency of DCs' operation, a dedicated investigation into the energy usage in DCs has been undertaken and a novel high performance dew point cooling system was introduced into a DC operational scheme. Based on the cooling load in DCs, a case study was carried out to evaluate the energy consumptions and energy usage effectiveness when using the novel dew point cooling system in different scales of DCs in various climates. It was found that by using the novel dew point cooling system, for 10 typical climates a DC can have a much lower power usage effectiveness (PUE) of 1.10 to 1.22 compared to that of 1.7 to 3.7 by using existing traditional cooling systems, leading to significantly increased energy efficiency of the DC operation. In addition, the energy performance by managing the cooling air supply at the different levels in DCs, i.e., room, row and rack level, was simulated by using a dynamic computer model. It was found that cooling air supply at rack level can provide a higher energy efficiency in DCs. Based on the above work, the energy saving potential in DCs was conducted by comparing DCs using an the novel dew point cooling system and the optimum management scheme for the cooling air supply to that using traditional air cooling systems and the same supply air management. Annual electricity consumptions for the two cases were given. It was found that by using the novel dew point cooling system and optimum management system for the cooling air supply, an 87.7~91.6% electricity consumption saving for space cooling in DCs could be achieved in 10 typical cities at 10 selected climatic conditions. [ABSTRACT FROM AUTHOR]

The energy consumption problem has become a bottleneck hindering further development of data centers. However, the heterogeneity of servers, hybrid cooling modes, and extra energy caused by system state transitions increases the complexity of the energy optimization problem. To deal with such challenges, in this paper, an Energy Aware Task Scheduling strategy (EATS) utilizing marginal cost and task classification method is proposed that cooperatively improves the energy efficiency of servers and cooling systems. An energy consumption model for servers, cooling systems, and state transition is developed, and the energy optimization problem in data centers is formulated. The concept of marginal cost is introduced to guide the task scheduling process. The task classification method is incorporated with the idea of marginal cost to further improve resource utilization and reduce the total energy consumption of data centers. Experiments are conducted using real-world traces, and energy reduction results are compared. Results show that EATS achieves more energy-savings of servers, cooling systems, state transition in comparison to the other two techniques under a various number of servers, cooling modules and task arrival intensities. It is validated that EATS is effective at reducing total energy consumption and improving the resource utilization of data centers. [ABSTRACT FROM AUTHOR]

The problem of high power consumption in data centers is becoming more and more prominent. In order to improve the energy efficiency of data centers, cooperatively optimizing the energy of IT systems and cooling systems has become an effective way. In this paper, a model-free deep reinforcement learning (DRL)-based joint optimization method MAD3C is developed to overcome the high-dimensional state and action space problems of the data center energy optimization. A hybrid AC-DDPG cooperative multi-agent framework is devised for the improvement of the cooperation between the IT and cooling systems for further energy efficiency improvement. In the framework, a scheduling baseline comparison method is presented to enhance the stability of the framework. Meanwhile, an adaptive score is designed for the architecture in consideration of multi-dimensional resources and resource utilization improvement. Experiments show that our proposed approach can effectively reduce energy for data centers through the cooperative optimization while guaranteeing training stability and improving resource utilization. [ABSTRACT FROM AUTHOR]

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%. [ABSTRACT FROM AUTHOR]

Removing heat from high-density information technology (IT) equipment is essential for data centers. Maintaining the proper operating environment for IT equipment can be expensive. Rising energy cost and energy consumption has prompted data centers to consider hot aisle and cold aisle containment strategies, which can improve the energy efficiency and maintain the recommended level of inlet air temperature to IT equipment. It can also resolve hot spots in traditional uncontained data centers to some degree. This study analyzes the IT environment of the hot aisle containment (HAC) system, which has been considered an essential solution for high-density data centers. The thermal performance was analyzed for an IT server room with HAC in a reference data center. Computational fluid dynamics analysis was conducted to compare the operating performances of the cooling air distribution systems applied to the raised and hard floors and to examine the difference in the IT environment between the server rooms. Regarding operating conditions, the thermal performances in a state wherein the cooling system operated normally and another wherein one unit had failed were compared. The thermal performance of each alternative was evaluated by comparing the temperature distribution, airflow distribution, inlet air temperatures of the server racks, and recirculation ratio from the outlet to the inlet. In conclusion, the HAC system with a raised floor has higher cooling efficiency than that with a hard floor. The HAC with a raised floor over a hard floor can improve the air distribution efficiency by 28%. This corresponds to 40% reduction in the recirculation ratio for more than 20% of the normal cooling conditions. The main contribution of this paper is that it realistically implements the effectiveness of the existing theoretical comparison of the HAC system by developing an accurate numerical model of a data center with a high-density fifth-generation (5G) environment and applying the operating conditions. [ABSTRACT FROM AUTHOR]

In data centers, efficient cooling systems are required to both keep the energy consumption as low as possible and to fulfill the temperature requirements. The aim of this work is to numerically investigate the effects of using partial aisle containment between the server racks for hard and raised floor configurations. The computational fluid dynamics (CFD) software ANSYS CFX was used together with the Reynolds stress turbulence model to perform the simulations. Velocity measurements in a server room were used for validation. Boundary conditions and the load of each rack were also retrieved from the experimental facility, implying an uneven load between the racks. A combination of the performance metrics Rack Cooling Index (RCI), Return Temperature Index (RTI) and Capture Index (CI) were used to evaluate the performance of the cooling systems for two supply flow rates at a 100% and 50% of operating condition. Based on the combination of performance metrics, the airflow management was improved in the raised floor configurations. With the supply flow rate set to operating conditions, the RCI was 100% for both raised floor and hard floor setups. The top- or side-cover fully prevented recirculation for the raised floor configuration, while it reduced the recirculation for the hard floor configuration. However, the RTI was low, close to 40% in the hard floor case, indicating poor energy efficiency. With the supply flow rate decreasing with 50%, the RTI increased to above 80%. Recirculation of hot air was indicated for all the containments when the supply rate was 50%, but the values of RCI still indicated an acceptable performance of the cooling system. [ABSTRACT FROM AUTHOR]