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).

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.

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 Efficient Data Centers Using Evaporative Cooling and Air Side Economizers

2011 ◽  
Author(s):  
Madhusudan Iyengar ◽  
Roger Schmidt
Keyword(s):  
Air Temperature ◽  
Data Center ◽  
Energy Use ◽  
Data Centers ◽  
Energy Savings ◽  
Transfer Functions ◽  
Water Evaporation ◽  
Outdoor Air ◽  
Data Center Cooling ◽  
The Usa

Information Technology (IT) data centers consume a large amount of electricity in the US and world-wide. Cooling has been found to contribute about one third of this energy use. The two primary contributors to the data center cooling energy use are the refrigeration chiller (about 50% of cooling) and the Computer Room Air Conditioning units (about 33% of cooling). This paper focuses on a data center configuration that eliminates the use of the chiller plant thereby yielding substantial energy savings. One method of eliminating the chiller plant is to directly pump outdoor air into a data center with some amount of conditioning (particulate filtration). This configuration is can be called Direct Air Side Economizer (ASE). Since computer equipment is usually designed with the assumption that the rack air inlet temperatures are in the 15–32 °C range, the use of ASE is constrained to use only in those geographies where the outdoor air conditions allow such direct air use. One method to reduce the sensible air temperature of the outdoor air that is being ducted into a data center room is water evaporation directly into the air stream. Such a method can be called Evaporative Air Side Economizer (EASE). This paper discusses the benefits of EASE data center configurations in the context of the climate in the USA and realizable energy savings compared with traditional chiller plant based cooling loops. Hour by hour outdoor air temperature data for a typical year and psychometric charts are utilized in conjunction with simple transfer functions to model cooling via evaporative media. Phoenix, a US city in a hot climate is used to illustrate the use of the relatively new method of data center cooling. A comparison to the traditional chiller plant based approach resulted in about 30% of energy savings at the data center level.

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.

scholarly journals Thermal Performance Evaluation of a Data Center Cooling System under Fault Conditions

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2996 ◽  
Author(s):  
Jinkyun Cho ◽  
Beungyong Park ◽  
Yongdae Jeong
Keyword(s):  
Water Supply ◽  
Thermal Performance ◽  
Data Center ◽  
Temperature Increase ◽  
Data Centers ◽  
Cooling System ◽  
Backup System ◽  
Air Supply ◽  
Chilled Water ◽  
Rapid Temperature

If a data center experiences a system outage or fault conditions, it becomes difficult to provide a stable and continuous information technology (IT) service. Therefore, it is critical to design and implement a backup system so that stability can be maintained even in emergency (unforeseen) situations. In this study, an actual 20 MW data center project was analyzed to evaluate the thermal performance of an IT server room during a cooling system outage under six fault conditions. In addition, a method of organizing and systematically managing operational stability and energy efficiency verification was identified for data center construction in accordance with the commissioning process. Up to a chilled water supply temperature of 17 °C and a computer room air handling unit air supply temperature of 24 °C, the temperature of the air flowing into the IT server room fell into the allowable range specified by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers standard (18–27 °C). It was possible to perform allowable operations for approximately 320 s after cooling system outage. Starting at a chilled water supply temperature of 18 °C and an air supply temperature of 25 °C, a rapid temperature increase occurred, which is a serious cause of IT equipment failure. Due to the use of cold aisle containment and designs with relatively high chilled water and air supply temperatures, there is a high possibility that a rapid temperature increase inside an IT server room will occur during a cooling system outage. Thus, the backup system must be activated within 300 s. It is essential to understand the operational characteristics of data centers and design optimal cooling systems to ensure the reliability of high-density data centers. In particular, it is necessary to consider these physical results and to perform an integrated review of the time required for emergency cooling equipment to operate as well as the backup system availability time.

Effect of Thermal Characteristics of Electronic Enclosures on Dynamic Data Center Performance

2010 ◽  
Author(s):  
Mahmoud Ibrahim ◽  
Siddharth Bhopte ◽  
Bahgat Sammakia ◽  
Bruce Murray ◽  
Madhusudan Iyengar ◽  
...  
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Characteristic Curve ◽  
Thermal Characteristic ◽  
Thermal Characteristics ◽  
Thermal Mass ◽  
Model Case ◽  
Temperature Boundary ◽  
Data Center Cooling ◽  
Dimensional Parameters

Data centers are the facilities that house large number of computer servers that dissipate high power. Considering the dynamics of the data centers, their efficient thermal management is a big challenge that needs to be addressed. Computational analysis using a CFD code is very useful technique that helps the engineer to understand and solve the data center cooling problem. Several ongoing numerical modeling research efforts assume the computer room air conditioning (CRAC) units as fixed flow devices with constant temperature boundary condition. In reality, CRAC supply temperature is governed by the thermal characteristic curve, as specified by vendor. In this paper, study is presented by incorporating the CRAC thermal characteristic curve in the numerical model. Case studies are presented to show how the segregated high and low powered clusters in a data center may affect the supply temperatures from the CRAC in their vicinity. Another concern that is crucial in analyzing data centers performance precisely is the effect of buoyancy and thermal mass on the facility environment. In some cases, the effect of thermal mass and buoyancy may cause unexpected behaviors such as temperature overshoot or rapid variations in temperature. Non-dimensional parameters are used to demonstrate the effects of thermal mass and buoyancy.

scholarly journals Power consumption prediction in cloud data center using machine learning

2020 ◽  
Vol 10 (2) ◽  
pp. 1524 ◽  
Author(s):  
Deepika T. ◽  
Prakash P.
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Power Consumption ◽  
Data Center ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Providers ◽  
Business World ◽  
Cloud Data ◽  
Cloud Data Centers

The flourishing development of the cloud computing paradigm provides several services in the industrial business world. Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing. Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated. A diverse set of numerous connected devices, engaged with the ubiquitous cloud, results in unprecedented power utilization by the data centers, accompanied by increased carbon footprints. Nearly a million physical machines (PM) are running all over the data centers, along with (5 – 6) million virtual machines (VM). In the next five years, the power needs of this domain are expected to spiral up to 5% of global power production. The virtual machine power consumption reduction impacts the diminishing of the PM’s power, however further changing in power consumption of data center year by year, to aid the cloud vendors using prediction methods. The sudden fluctuation in power utilization will cause power outage in the cloud data centers. This paper aims to forecast the VM power consumption with the help of regressive predictive analysis, one of the Machine Learning (ML) techniques. The potency of this approach to make better predictions of future value, using Multi-layer Perceptron (MLP) regressor which provides 91% of accuracy during the prediction process.

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%.

Data Center Enhancement by Server Resources Utilization

2021 ◽  
Vol 39 (1B) ◽  
pp. 203-208
Author(s):  
Haider A. Ghanem ◽  
Rana F. Ghani ◽  
Maha J. Abbas
Keyword(s):  
Cloud Computing ◽  
Power Consumption ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Data Center ◽  
Data Centers ◽  
Virtual Machines ◽  
The Internet ◽  
Memory Resources

Data centers are the main nerve of the Internet because of its hosting, storage, cloud computing and other services. All these services require a lot of work and resources, such as energy and cooling. The main problem is how to improve the work of data centers through increased resource utilization by using virtual host simulations and exploiting all server resources. In this paper, we have considered memory resources, where Virtual machines were distributed to hosts after comparing the virtual machines with the host from where the memory and putting the virtual machine on the appropriate host, this will reduce the host machines in the data centers and this will improve the performance of the data centers, in terms of power consumption and the number of servers used and cost.

scholarly journals Open Source Monitoring System for IT Infrastructures Incorporating IoT-Based Sensors

Proceedings ◽  
2020 ◽  
Vol 54 (1) ◽  
pp. 56
Author(s):  
Alejandro Mosteiro Vázquez ◽  
Carlos Dafonte ◽  
Ángel Gómez
Keyword(s):  
Power Consumption ◽  
Open Source ◽  
Monitoring System ◽  
Data Center ◽  
Data Centers ◽  
Source Monitoring ◽  
State Of The Art ◽  
Memory Usage ◽  
Network Bandwidth ◽  
Status Data

This paper introduces the development of a data center monitoring system based on IoT technologies. The system is meant to work as an administrative tool for system administrators in any environment, but mainly focused on data centers, since it integrates sensor and server status data. We are developing a system that gives a broad view of a data center, integrating server data such as CPU and memory usage or network bandwidth with room health parameters such as temperature, humidity, and power consumption or the presence sensors that indicate if there were people inside the room at the time a certain event occurred. As this is a work in progress, in this paper, we present the state-of-the-art of this subject, as well as what we expect to obtain from this project.

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