Failure Resistant Data Center Cooling Control Through Model-Based Thermal Zone Mapping

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):  
Rongliang Zhou ◽  
Cullen Bash ◽  
Zhikui Wang ◽  
Alan McReynolds ◽  
Thomas Christian ◽  
...  

Data centers are large computing facilities that can house tens of thousands of computer servers, storage and networking devices. They can consume megawatts of power and, as a result, reject megawatts of heat. For more than a decade, researchers have been investigating methods to improve the efficiency by which these facilities are cooled. One of the key challenges to maintain highly efficient cooling is to provide on demand cooling resources to each server rack, which may vary with time and rack location within the larger data center. In common practice today, chilled water or refrigerant cooled computer room air conditioning (CRAC) units are used to reject the waste heat outside the data center, and they also work together with the fans in the IT equipment to circulate air within the data center for heat transport. In a raised floor data center, the cool air exiting the multiple CRAC units enters the underfloor plenum before it is distributed through the vent tiles in the cold aisles to the IT equipment. The vent tiles usually have fixed openings and are not adapted to accommodate the flow demand that can vary from cold aisle to cold aisle or rack to rack. In this configuration, CRAC units have the extra responsibilities of cooling resources distribution as well as provisioning. The CRAC unit, however, does not have the fine control granularity to adjust air delivery to individual racks since it normally affects a larger thermal zone, which consists of a multiplicity of racks arranged into rows. To better match cool air demand on a per cold aisle or rack basis, floor-mounted adaptive vent tiles (AVT) can be used to replace CRAC units for air delivery adjustment. In this arrangement, each adaptive vent tile can be remotely commanded from fully open to fully close for finer local air flow regulation. The optimal configuration for a multitude of AVTs in a data center, however, can be far from intuitive because of the air flow complexity. To unleash the full potential of the AVTs for improved air flow distribution and hence higher cooling efficiency, we propose a two-step approach that involves both steady-state and dynamic optimization to optimize the cooling resource provisioning and distribution within raised-floor air cooled data centers with rigid or partial containment. We first perform a model-based steady-state optimization to optimize whole data center air flow distribution. Within each cold aisle, all AVTs are configured to a uniform opening setting, although AVT opening may vary from cold aisle to cold aisle. We then use decentralized dynamic controllers to optimize the settings of each CRAC unit such that the IT equipment thermal requirement is satisfied with the least cooling power. This two-step optimization approach simplifies the large scale dynamic control problem, and its effectiveness in cooling efficiency improvement is demonstrated through experiments in a research data center.


Author(s):  
David Okposio ◽  
A. G. Agwu Nnanna ◽  
Harvey Abramowitz

Abstract The cooling effect of evaporative cooling systems is well documented in literature. Evaporative cooling however introduces humidity into the cooled space, which is unsuitable for data centers. Desiccants (liquid, solid or composites) adsorb moisture from the cooled air to control humidity and is regenerated using waste heat from the data center. This work is an experimental and theoretical investigation of the use of desiccant assisted evaporative cooling for data center cooling according to ASHRAE thermal guideline TC 9.9 . The thickness of the cooling pads is varied with specific surface area, velocity of air through the pad measured, the product of the air velocity and surface area yields the volumetric flowrate of the air, the water flow rate varied as well. The configuration is such that the rotary desiccant wheel (impregnated with silica gel) comes after the evaporative cooler. A novel water recovery system using the Peltier effect is proposed to recover moisture from the return air stream thereby optimizing the water consumption of evaporative cooling technology and providing suitable air quality for data center cooling.


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):  
Rongliang Zhou ◽  
Zhikui Wang ◽  
Cullen E. Bash ◽  
Alan McReynolds

In traditional raised-floor data center design with hot aisle and cold aisle separation, the cooling efficiency suffers from recirculation resulting from the mixing of cool air from the Computer Room Air Conditioning (CRAC) units and the hot exhaust air exiting from the back of the server racks. To minimize recirculation and hence increase cooling efficiency, hot aisle containment has been employed in an increasing number of data centers. Based on the underlying heat transfer principles, we present in this paper a dynamic model for cooling management in both open and contained environment, and propose decentralized model predictive controllers (MPC) for control of the CRAC units. One approach to partition a data center into overlapping CRAC zones of influence is discussed. Within each zone, the CRAC unit blower speed and supply air temperature are adjusted by a MPC controller to regulate the rack inlet temperatures, while minimizing the cooling power consumption. The proposed decentralized cooling control approach is validated in a production data center with hot aisles contained by plastic strips. Experimental results demonstrate both its stability and ability to reject various disturbances.


2018 ◽  
Vol 7 (3.4) ◽  
pp. 113
Author(s):  
T Suresh ◽  
Dr A. Murugan

In all types of data center, keeping the right temperature with less cost and energy is one of important objective as energy saving is crucial in increased data driven industry. Energy saving is global focus for all industry. In Information technology, more than 60% of energy is utilized in data centers as it needs to be up and running. As per Avocent data center issue study, across globe more than 54% of data centers are in redesigning process to improve their efficiency and reduce operational cost and energy consumption. Data center managers and operators major challenge was how to maintain the temperature of servers with less power and energy. When the densities of data center energy nearing 5 kilowatts (kW) per cabinet, organizations are trying to find a way to manage the heat through latest technologies. Power usage per square can be reduced by incorporating liquid-cooling devices instead of increasing airflow volume. This is especially important in a data center with a typical under-floor cooling system. This research paper uses Rear-Door Heat eXchangers (RDHx) and cool logic solutions to reduce energy consumption. It gives result of implementation of Cold Logik and RDHx solution to Data center and proves that how it saves energy and power. Data center has optimized space, cooling, power and operational cost by implementing RDHx technology. This will enable to add more servers without increasing the space and reduce cooling and power cost. It also saves Data center space from heat dissipation from servers.  


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.


Author(s):  
Tianyi Gao ◽  
James Geer ◽  
Bahgat G. Sammakia ◽  
Russell Tipton ◽  
Mark Seymour

Cooling power constitutes a large portion of the total electrical power consumption in data centers. Approximately 25%∼40% of the electricity used within a production data center is consumed by the cooling system. Improving the cooling energy efficiency has attracted a great deal of research attention. Many strategies have been proposed for cutting the data center energy costs. One of the effective strategies for increasing the cooling efficiency is using dynamic thermal management. Another effective strategy is placing cooling devices (heat exchangers) closer to the source of heat. This is the basic design principle of many hybrid cooling systems and liquid cooling systems for data centers. Dynamic thermal management of data centers is a huge challenge, due to the fact that data centers are operated under complex dynamic conditions, even during normal operating conditions. In addition, hybrid cooling systems for data centers introduce additional localized cooling devices, such as in row cooling units and overhead coolers, which significantly increase the complexity of dynamic thermal management. Therefore, it is of paramount importance to characterize the dynamic responses of data centers under variations from different cooling units, such as cooling air flow rate variations. In this study, a detailed computational analysis of an in row cooler based hybrid cooled data center is conducted using a commercially available computational fluid dynamics (CFD) code. A representative CFD model for a raised floor data center with cold aisle-hot aisle arrangement fashion is developed. The hybrid cooling system is designed using perimeter CRAH units and localized in row cooling units. The CRAH unit supplies centralized cooling air to the under floor plenum, and the cooling air enters the cold aisle through perforated tiles. The in row cooling unit is located on the raised floor between the server racks. It supplies the cooling air directly to the cold aisle, and intakes hot air from the back of the racks (hot aisle). Therefore, two different cooling air sources are supplied to the cold aisle, but the ways they are delivered to the cold aisle are different. Several modeling cases are designed to study the transient effects of variations in the flow rates of the two cooling air sources. The server power and the cooling air flow variation combination scenarios are also modeled and studied. The detailed impacts of each modeling case on the rack inlet air temperature and cold aisle air flow distribution are studied. The results presented in this work provide an understanding of the effects of air flow variations on the thermal performance of data centers. The results and corresponding analysis is used for improving the running efficiency of this type of raised floor hybrid data centers using CRAH and IRC units.


Author(s):  
Kamran Nazir ◽  
Naveed Durrani ◽  
Imran Akhtar ◽  
M. Saif Ullah Khalid

Due to high energy demands of data centers and the energy crisis throughout the world, efficient heat transfer in a data center is an active research area. Until now major emphasis lies upon study of air flow rate and temperature profiles for different rack configurations and tile layouts. In current work, we consider different hot aisle (HA) and cold aisle (CA) configurations to study heat transfer phenomenon inside a data center. In raised floor data centers when rows of racks are parallel to each other, in a conventional cooling system, there are equal number of hot and cold aisles for odd number of rows of racks. For even number of rows of racks, whatever configuration of hot/cold aisles is adopted, number of cold aisles is either one greater or one less than number of hot aisles i.e. two cases are possible case A: n(CA) = n(HA) + 1 and case B: n(CA) = n(HA) − 1 where n(CA), n(HA) denotes number of cold and hot aisles respectively. We perform numerical simulations for two (case1) and four (case 2) racks data center. The assumption of constant pressure below plenum reduces the problem domain to above plenum area only. In order to see which configuration provides higher heat transfer across servers, we measure heat transfer across servers on the basis of temperature differences across racks, and in order to validate them, we find mass flow rates on rack outlet. On the basis of results obtained, we conclude that for even numbered rows of rack data center, using more cold aisles than hot aisles provide higher heat transfer across servers. These results provide guidance on the design and layout of a data center.


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