Data Center Cooling Efficiency With Simulation-Based Optimization

Author(s):  
Laurent M. Billet ◽  
Christopher M. Healey ◽  
James W. VanGilder ◽  
Zachary M. Pardey

The efficient control of cooling for data centers is an issue of broad economic importance due to the significant energy consumption of data centers. Many solutions attempt to optimize the control of the cooling equipment with temperature, pressure, or airflow sensors. We propose a simulation-based approach to optimize the cooling energy consumption and show how this approach can be implemented with simple power-consumption models. We also provide a real-life case study to demonstrate how energy saving cooling setpoints can be found using calibrated simulations and smooth metamodels of the system.

Author(s):  
Madhusudan Iyengar ◽  
Roger R. Schmidt

The increasingly ubiquitous nature of computer and internet usage in our society, has driven advances in semiconductor technology, server packaging, and cluster level optimizations, in the IT industry. Not surprisingly this has an impact on our societal infrastructure with respect to providing the requisite energy to fuel these power hungry machines. Cooling has been found to contribute to about a third of the total data center energy consumption, and is the focus of this study. In this paper we develop and present physics based models to allow the prediction of the energy consumption and heat transfer phenomenon in a data center. These models allow the estimation of the microprocessor junction and server inlet air temperatures for different flow and temperature conditions at various parts of the data center cooling infrastructure. For a case study example considered, the chiller energy use was the biggest fraction of about 41% and also the most inefficient. The room air conditioning was the second largest energy component and also the second most inefficient. A sensitivity analysis of plant and chiller energy efficiency with chiller set point temperature and outdoor air conditions is also presented.


2009 ◽  
Vol 131 (2) ◽  
Author(s):  
Madhusudan Iyengar ◽  
Roger Schmidt

The increasingly ubiquitous nature of computer and internet usage in our society has driven advances in semiconductor technology, server packaging, and cluster level optimizations in the IT industry. Not surprisingly this has an impact on our societal infrastructure with respect to providing the requisite energy to fuel these power hungry machines. Cooling has been found to contribute about a third of the total data center energy consumption and is the focus of this study. In this paper we develop and present physics based models to allow the prediction of the energy consumption and heat transfer phenomenon in a data center. These models allow the estimation of the microprocessor junction and server inlet air temperatures for different flows and temperature conditions at various parts of the data center cooling infrastructure. For the case study example considered, the chiller energy use was the biggest fraction of about 41% and was also the most inefficient. The room air conditioning was the second largest energy component and was also the second most inefficient. A sensitivity analysis of plant and chiller energy efficiencies with chiller set point temperature and outdoor air conditions is also presented.


2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Dustin W. Demetriou ◽  
H. Ezzat Khalifa

The work presented in this paper describes a simplified thermodynamic model that can be used for exploring optimization possibilities in air-cooled data centers. The model is used to evaluate parametrically the total energy consumption of the data center cooling infrastructure for data centers that utilize aisle containment. The analysis highlights the importance of reducing the total power required for moving the air within the computer room air conditioners (CRACs), the plenum, and the servers, rather than focusing primarily or exclusively on reducing the refrigeration system’s power consumption. In addition, the benefits of introducing a bypass recirculation branch in enclosed aisle configurations are shown. The analysis shows a potential for as much as a 60% savings in cooling infrastructure energy consumption by utilizing an optimized enclosed aisle configuration with bypass recirculation, instead of a traditional enclosed aisle in which all the data center exhaust is forced to flow through the CRACs. Furthermore, computational fluid dynamics is used to evaluate practical arrangements for implementing bypass recirculation in raised floor data centers. A configuration where bypass tiles, with controllable low-lift fans, are placed close to the discharge of CRACs results in increased mixing and is shown to be a suitable method for providing nearly thermally uniform conditions to the inlet of the servers in an enclosed cold aisle. Other configurations of bypass implementation are also discussed and explored.


Author(s):  
Stephen Paul Linder ◽  
Jim Van Gilder ◽  
Yan Zhang ◽  
Enda Barrett

Abstract Efficient cooling of data center infrastructure is an important way to reduce total energy consumption. Containment, with separation of hot and cold airflows has allowed significant increase in efficiencies. However, balancing the airflow, so that IT equipment in an aisle only receives the cooling airflow that that aisle needs is still often not done. We propose a new architecture where IT racks are clustered together with shared hot aisles ducted to a common ceiling plenum. Each aisle has an actively controlled damper used to balance the airflow to the cooling infrastructure. Using a differential air pressure sensor in each aisle and an algorithm designed to balance the flow network, we minimize the cooling airflow and maximize cooling efficiency.


Author(s):  
Rongliang Zhou ◽  
Zhikui Wang ◽  
Cullen E. Bash ◽  
Tahir Cader ◽  
Alan McReynolds

Due to the tremendous cooling costs, data center cooling efficiency improvement has been actively pursued for years. In addition to cooling efficiency, the reliability of the cooling system is also essential for guaranteed uptime. In traditional data center cooling system design with N+1 or higher redundancy, all the computer room air conditioning (CRAC) units are either constantly online or cycled according to a predefined schedule. Both cooling system configurations, however, have their respective drawbacks. Data centers are usually over provisioned when all CRAC units are online all the time, and hence the cooling efficiency is low. On the other hand, although cooling efficiency can be improved by cycling CRAC units and turning off the backups, it is difficult to schedule the cycling such that sufficient cooling provisioning is guaranteed and gross over provisioning is avoided. In this paper, we aim to maintain the data center cooling redundancy while achieving high cooling efficiency. Using model-based thermal zone mapping, we first partition data centers to achieve the desired level of cooling influence redundancy. We then design a distributed controller for each of the CRAC units to regulate the thermal status within its zone of influence. The distributed controllers coordinate with each other to achieve the desired data center thermal status using the least cooling power. When CRAC units or their associated controllers fail, racks in the affected thermal zones are still within the control “radius” of other decentralized cooling controllers through predefined thermal zone overlap, and hence their thermal status is properly managed by the active CRAC units and controllers. Using this failure resistant data center cooling control approach, both cooling efficiency and robustness are achieved simultaneously. A higher flexibility in cooling system maintenance is also expected, since the distributed control system can automatically adapt to the new cooling facility configuration incurred by maintenance.


Author(s):  
Uschas Chowdhury ◽  
Manasa Sahini ◽  
Ashwin Siddarth ◽  
Dereje Agonafer ◽  
Steve Branton

Modern day data centers are operated at high power for increased power density, maintenance, and cooling which covers almost 2 percent (70 billion kilowatt-hours) of the total energy consumption in the US. IT components and cooling system occupy the major portion of this energy consumption. Although data centers are designed to perform efficiently, cooling the high-density components is still a challenge. So, alternative methods to improve the cooling efficiency has become the drive to reduce the cooling cost. As liquid cooling is more efficient for high specific heat capacity, density, and thermal conductivity, hybrid cooling can offer the advantage of liquid cooling of high heat generating components in the traditional air-cooled servers. In this experiment, a 1U server is equipped with cold plate to cool the CPUs while the rest of the components are cooled by fans. In this study, predictive fan and pump failure analysis are performed which also helps to explore the options for redundancy and to reduce the cooling cost by improving cooling efficiency. Redundancy requires the knowledge of planned and unplanned system failures. As the main heat generating components are cooled by liquid, warm water cooling can be employed to observe the effects of raised inlet conditions in a hybrid cooled server with failure scenarios. The ASHRAE guidance class W4 for liquid cooling is chosen for our experiment to operate in a range from 25°C – 45°C. The experiments are conducted separately for the pump and fan failure scenarios. Computational load of idle, 10%, 30%, 50%, 70% and 98% are applied while powering only one pump and the miniature dry cooler fans are controlled externally to maintain constant inlet temperature of the coolant. As the rest of components such as DIMMs & PCH are cooled by air, maximum utilization for memory is applied while reducing the number fans in each case for fan failure scenario. The components temperatures and power consumption are recorded in each case for performance analysis.


2021 ◽  
Author(s):  
Ladan Vahidi-Arbabi

Thermal performance of complex buildings like data centers is not easy to evaluate. Experimental Investigation of the effects of energy conservation methods or any alteration that might occur in hundreds of variables in data centres would cost stakeholders time and money. And they might find worthless at times. Building energy model is a well-established field of science with an insufficient number of applications in data centers. This study presents methods of developing a data center model based on an actual case study. Moreover, it identifies effective calibrating strategies to increase the model performance accuracy relative to a recorded dataset. A reliable energy model can assist data center operators and researchers in different ways. As a result, calibrated energy model proved Earth Rangers’ data center can be independent of a heat pump or chiller use for most of the year, while ground heat exchangers deliver excessive heat to the ground as the heat sink.


Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah

Cloud computing aims to migrate IT services to distant data centers in order to reduce the dependency of the services on the limited local resources. Cloud computing provides access to distant computing resources via Web services while the end user is not aware of how the IT infrastructure is managed. Besides the novelties and advantages of cloud computing, deployment of a large number of servers and data centers introduces the challenge of high energy consumption. Additionally, transportation of IT services over the Internet backbone accumulates the energy consumption problem of the backbone infrastructure. In this chapter, the authors cover energy-efficient cloud computing studies in the data center involving various aspects such as: reduction of processing, storage, and data center network-related power consumption. They first provide a brief overview of the existing approaches on cool data centers that can be mainly grouped as studies on virtualization techniques, energy-efficient data center network design schemes, and studies that monitor the data center thermal activity by Wireless Sensor Networks (WSNs). The authors also present solutions that aim to reduce energy consumption in data centers by considering the communications aspects over the backbone of large-scale cloud systems.


Author(s):  
N. Fumo ◽  
V. Bortone ◽  
J. C. Zambrano

Data centers are facilities that primarily contain electronic equipment used for data processing, data storage, and communications networking. Regardless of their use and configuration, most data centers are more energy intensive than other buildings. The continuous operation of Information Technology equipment and power delivery systems generates a significant amount of heat that must be removed from the data center for the electronic equipment to operate properly. Since data centers spend up to half their energy on cooling, cooling systems becomes a key factor for energy consumption reduction strategies and alternatives in data centers. This paper presents a theoretical analysis of an absorption chiller driven by solar thermal energy as cooling plant alternative for data centers. Source primary energy consumption is used to compare the performance of different solar cooling plants with a standard cooling plant. The solar cooling plants correspond to different combinations of solar collector arrays and thermal storage tank, with a boiler as source of energy to ensure continuous operation of the absorption chiller. The standard cooling plant uses an electric chiller. Results suggest that the solar cooling plant with flat-plate solar collectors is a better option over the solar cooling plant with evacuated-tube solar collectors. However, although solar cooling plants can decrease the primary energy consumption when compared with the standard cooling plant, the net present value of the cost to install and operate the solar cooling plants are higher than the one for the standard cooling plant.


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