Energy Modeling of Air-Cooled Data Centers: Part I—The Optimization of Enclosed Aisle Configurations

2011 ◽  
Author(s):  
Dustin W. Demetriou ◽  
H. Ezzat Khalifa
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Temperature Rise ◽  
Data Center ◽  
Data Centers ◽  
Total Power ◽  
Optimum Operating ◽  
Cooling Power ◽  
Inlet Temperature ◽  
Total Energy Consumption

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 parametrically evaluate 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 CRACs, the plenum, and the servers, rather than focusing primarily or exclusively on reducing the refrigeration system’s power consumption and shows the benefits of bypass recirculation in enclosed aisle configurations. The analysis shows a potential for as much as a 57% savings in cooling infrastructure energy consumption by utilizing an optimized enclosed aisle configuration with bypass recirculation, instead of a traditional enclosed aisle, where all the data center exhaust is forced to flow through the computer room air conditioners (CRACs), for racks with a modest temperature rise (∼10°C). However, for racks with larger temperature rise (> ∼20°C), the saving are less than 5%. Furthermore, for servers whose fan speed (flow rate) varies as a function of inlet temperature, the analysis shows that the optimum operating regime for enclosed aisle data centers falls within a very narrow band and that power reductions are possible by lowering the uniform server inlet temperature in the enclosed aisle from 27°C to 22°C. However, the optimum CRAC exit temperature over the 22-to-27°C range of enclosed cold aisle temperature falls between ∼16 and 20°C because a significant reduction in the power consumption is possible through the use of bypass recirculation. Without bypass recirculation, the power consumption for a server inlet temperature of 22°C enclosed aisle case with a server temperature rise of 10°C would be a whopping 43% higher than with bypass recirculation. It is worth noting that, without bypass recirculation maintaining the enclosed cold aisle at 22°C instead of 27°C would reduce power consumption by 48%. It is also shown that enclosing the aisles together with bypass recirculation (when beneficial) also reduces the dependence of the optimum cooling power on server temperature rise.

Energy Optimization of Air-Cooled Data Centers

2010 ◽  
Vol 2 (4) ◽  
Author(s):  
H. E. Khalifa ◽  
D. W. Demetriou
Keyword(s):  
Power Consumption ◽  
Temperature Rise ◽  
Data Center ◽  
Data Centers ◽  
Optimal Operation ◽  
Effect Of Temperature ◽  
Cooling Power ◽  
Air Conditioners ◽  
Air Supply ◽  
Operating Strategies

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 has been used to identify optimal, energy-efficient designs, operating scenarios, and operating parameters such as flow rates and air supply temperatures. The results of this analysis highlight the important features that need to be considered when optimizing the operation of air-cooled data centers, especially the trade-off between low air supply temperature and increased air flow rate. The model was shown to be especially valuable in defining the optimal operating strategies for enclosed aisle configurations with fixed and variable server flows, and to elucidate the deleterious effect of temperature nonuniformity at the inlet of the racks on the data center cooling infrastructure power consumption. The analysis shows a potential for as much as an ∼58% savings in cooling infrastructure energy consumption by utilizing an optimized enclosed aisle configuration with bypass recirculation, instead of a traditional enclosed aisle, where all the data center exhaust is forced to flow through the computer room air conditioners. The analysis of open-aisle data centers shows that as the temperature at the inlet of the racks becomes more nonuniform, optimal operation tends toward lower recirculation and higher power consumption; again, stressing the importance of providing as uniform a temperature to the racks as possible. It is also revealed that servers with a modest temperature rise (∼10°C) have a wider latitude for cooling infrastructure optimization than those with a high temperature rise (≥20°C), which tend to consume less cooling power when the aisles are enclosed.

Genetic algorithm based cooling energy optimization of data centers

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jayati Athavale ◽  
Minami Yoda ◽  
Yogendra Joshi
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Power Consumption ◽  
Data Center ◽  
Load Distribution ◽  
Data Centers ◽  
Cooling Power ◽  
Temperature Prediction ◽  
Content Type ◽  
Optimization Framework

Purpose This study aims to present development of genetic algorithm (GA)-based framework aimed at minimizing data center cooling energy consumption by optimizing the cooling set-points while ensuring that thermal management criteria are satisfied. Design/methodology/approach Three key components of the developed framework include an artificial neural network-based model for rapid temperature prediction (Athavale et al., 2018a, 2019), a thermodynamic model for cooling energy estimation and GA-based optimization process. The static optimization framework informs the IT load distribution and cooling set-points in the data center room to simultaneously minimize cooling power consumption while maximizing IT load. The dynamic framework aims to minimize cooling power consumption in the data center during operation by determining most energy-efficient set-points for the cooling infrastructure while preventing temperature overshoots. Findings Results from static optimization framework indicate that among the three levels (room, rack and row) of IT load distribution granularity, Rack-level distribution consumes the least cooling power. A test case of 7.5 h implementing dynamic optimization demonstrated a reduction in cooling energy consumption between 21%–50% depending on current operation of data center. Research limitations/implications The temperature prediction model used being data-driven, is specific to the lab configuration considered in this study and cannot be directly applied to other scenarios. However, the overall framework can be generalized. Practical implications The developed framework can be implemented in data centers to optimize operation of cooling infrastructure and reduce energy consumption. Originality/value This paper presents a holistic framework for improving energy efficiency of data centers which is of critical value given the high (and increasing) energy consumption by these facilities.

Optimization of Enclosed Aisle Data Centers Using Bypass Recirculation

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Dustin W. Demetriou ◽  
H. Ezzat Khalifa
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Energy Consumption ◽  
Data Center ◽  
Data Centers ◽  
Total Power ◽  
Total Energy Consumption ◽  
Air Conditioners ◽  
Data Center Cooling ◽  
Flow Through

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.

Energy Modeling of Air-Cooled Data Centers: Part II—The Effect of Recirculation on the Energy Optimization of Open-Aisle, Air-Cooled Data Centers

2011 ◽  
Author(s):  
Dustin W. Demetriou ◽  
H. Ezzat Khalifa
Keyword(s):  
Power Consumption ◽  
Temperature Rise ◽  
Data Center ◽  
Data Centers ◽  
Energy Savings ◽  
Optimal Operation ◽  
Effect Of Temperature ◽  
Total Energy Consumption ◽  
Air Supply ◽  
Data Center Cooling

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 has been used to identify optimal, energy-efficient designs, operating scenarios, and operating parameters such as flow rates and air supply temperature. The model is used to parametrically evaluate the total energy consumption of the data center cooling infrastructure, by considering changes in the server temperature rise. The results of this parametric analysis highlight the important features that need to be considered when optimizing the operation of air-cooled data centers, especially the trade-off between low air supply temperature and increased air flow rate. The analysis is used to elucidate the deleterious effect of temperature non-uniformity at the inlet of the racks on the data center cooling infrastructure power consumption. A recirculation non-uniformity metric, θ, is introduced, which is the ratio of the maximum recirculation of any server to the average recirculation of all servers. The analysis of open-aisle data centers shows that as the recirculation non-uniformity at the inlet of the racks increases, optimal operation tends toward lower recirculation and higher power consumption; stressing the importance of providing as uniform conditions to the racks as possible. Cooling infrastructure energy savings greater than 40% are possible for a data center with uniform recirculation (θ = 0) compared to a data center with a typical recirculation non-uniformity (θ = 4). It is also revealed that servers with a modest temperature rise (∼10°C) have a wider latitude for cooling optimization than those with a high temperature rise (≥20°C).

Characterization of an Isolated Hybrid Cooled Server With Failure Scenarios Using Warm Water Cooling

2017 ◽  
Author(s):  
Uschas Chowdhury ◽  
Manasa Sahini ◽  
Ashwin Siddarth ◽  
Dereje Agonafer ◽  
Steve Branton
Keyword(s):  
Energy Consumption ◽  
Data Centers ◽  
Cooling System ◽  
Warm Water ◽  
Alternative Methods ◽  
Inlet Temperature ◽  
Cooling Efficiency ◽  
Water Cooling ◽  
Liquid Cooling ◽  
Total Energy Consumption

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.

scholarly journals Impact of Fan Airflow of IT Equipment on Thermal Environment and Energy Consumption of a Data Center

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6166
Author(s):  
Naoki Futawatari ◽  
Yosuke Udagawa ◽  
Taro Mori ◽  
Hirofumi Hayama
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Data Center ◽  
Air Conditioning ◽  
Thermal Environment ◽  
Operating Efficiency ◽  
Inlet Temperature ◽  
Total Energy Consumption ◽  
Air Supply ◽  
Machine Room

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%.

scholarly journals Intra- and Inter-Server Smart Task Scheduling for Profit and Energy Optimization of HPC Data Centers

2020 ◽  
Vol 10 (4) ◽  
pp. 32
Author(s):  
Sayed Ashraf Mamun ◽  
Alexander Gilday ◽  
Amit Kumar Singh ◽  
Amlan Ganguly ◽  
Geoff V. Merrett ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Data Center ◽  
High Performance ◽  
Data Centers ◽  
Virtual Machines ◽  
For Profit ◽  
Dynamic Voltage ◽  
High Power Consumption ◽  
Performance Computing

Servers in a data center are underutilized due to over-provisioning, which contributes heavily toward the high-power consumption of the data centers. Recent research in optimizing the energy consumption of High Performance Computing (HPC) data centers mostly focuses on consolidation of Virtual Machines (VMs) and using dynamic voltage and frequency scaling (DVFS). These approaches are inherently hardware-based, are frequently unique to individual systems, and often use simulation due to lack of access to HPC data centers. Other approaches require profiling information on the jobs in the HPC system to be available before run-time. In this paper, we propose a reinforcement learning based approach, which jointly optimizes profit and energy in the allocation of jobs to available resources, without the need for such prior information. The approach is implemented in a software scheduler used to allocate real applications from the Princeton Application Repository for Shared-Memory Computers (PARSEC) benchmark suite to a number of hardware nodes realized with Odroid-XU3 boards. Experiments show that the proposed approach increases the profit earned by 40% while simultaneously reducing energy consumption by 20% when compared to a heuristic-based approach. We also present a network-aware server consolidation algorithm called Bandwidth-Constrained Consolidation (BCC), for HPC data centers which can address the under-utilization problem of the servers. Our experiments show that the BCC consolidation technique can reduce the power consumption of a data center by up-to 37%.

Review on Cooling System Energy Consumption in Internet Data Centers

2016 ◽  
Vol 24 (04) ◽  
pp. 1630008 ◽  
Author(s):  
Kofi Owura Amoabeng ◽  
Jong Min Choi
Keyword(s):  
Energy Consumption ◽  
Data Center ◽  
Energy Demand ◽  
Data Centers ◽  
Cooling System ◽  
High Heat ◽  
Total Energy Consumption ◽  
It Industry ◽  
Public And Private ◽  
Conventional Cooling

Due to the advancement of the telecommunication and information technology (IT) industry, internet data centers (IDCs) have become widespread in the public and private sectors. As such, energy demand in the center has also become increasingly prominent. Several technologies on energy management have been studied to determine the options available to minimize the energy required to operate the data center as well as reduce greenhouse gas emissions. The cooling system is required to remove the high heat dissipated by the IT electronic components especially the servers in order to ensure safe and reliable working condition. However, it utilizes more than one-third of the total energy consumption in the data center. In this study, the energy efficiency technologies that are usually applied to cooling systems in data centers were reviewed. The aim is to find out the strategies that will reduce the energy consumption of the cooling system since the cooling demand in data center is all year round. Prior to that, the performance metric tool that is mostly used in analyzing data center efficiency was discussed. The conventional cooling system technologies that are utilized in data centers were also provided. Lastly, innovative cooling technologies for future solutions in data centers were discussed.

Dynamic Control of Airflow Balance in Data Centers

2019 ◽  
Author(s):  
Stephen Paul Linder ◽  
Jim Van Gilder ◽  
Yan Zhang ◽  
Enda Barrett
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Pressure Sensor ◽  
Data Center ◽  
Data Centers ◽  
Dynamic Control ◽  
Air Pressure ◽  
Cooling Efficiency ◽  
Total Energy Consumption ◽  
Flow Network

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.

scholarly journals Cold LOGIK and RDHX Solution for Data Center Energy Optimization

2018 ◽  
Vol 7 (3.4) ◽  
pp. 113
Author(s):  
T Suresh ◽  
Dr A. Murugan
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Data Center ◽  
Data Centers ◽  
Heat Dissipation ◽  
Cooling System ◽  
Cooling Power ◽  
Operational Cost ◽  
Power Cost ◽  
The Right

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.  

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