Analytical Modeling for Thermodynamic Characterization of Data Center Cooling Systems

Iyengar, Madhusudan; Schmidt, Roger

doi:10.1115/1.3103952

Cited by 49 publications

(26 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are a number of works concentrating on energy-minimization techniques for air cooling systems. For instance, Iyengar and Schmid [8] modeled energy consumption for every component based on physics. They also formulated a holistic energy model of HVAC subsystem by adding up the energy of overall components within a cooling system.…”

Section: Cooling Subsystem Managementmentioning

confidence: 99%

“…There are a number of studies separately dealing with energy minimization in data centers. For example, [2][3][4][5][6] studied IT energy consumption, others [7][8][9] inclined to optimize cooling energy consumption. However, the aforementioned studies only concentrated on the energy consumption of a subset of system components and overlooked the interactions among them.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic thermal and IT resource management strategies for data center energy minimization

Wan

Yang³

et al. 2017

J Cloud Comp

View full text Add to dashboard Cite

Energy-hungry data centers attract researchers' attention to energy consumption minimization-a challenge confronted by both industry and academia. To assure the server reliability, its instantaneous temperature is generally controlled within a preset threshold. Nonetheless, field studies indicated that the occasional violation of extreme temperature constraints hardly affect the system reliability in practice. Therefore, strictly restraining the server temperature may contribute to meaningless energy consumption. As a response to this limitation, this paper presents a dynamic control algorithm without violating the average temperature constraint. We formulate a "soft" Server Temperature-Constrained Energy Minimization (STCEM) problem, where the object function consists of IT and Heat Ventilation & Air Conditioner (HVAC) energy. Based on the Lyapunov optimization, two algorithms, i.e., linear and quadratic control policies, are proposed to approximately solve the STCEM problem. The non-negative weight parameter V is introduced to trade off the energy consumption against server temperature constraint. Furthermore, extensive simulations have been carried out to evaluate the system performance for the proposed controlled algorithms. The experimental results demonstrate that the quadratic control policy outperforms the linear counterpart on the STCEM problem. Specifically, the energy consumption and server temperature constraint are well balanced when V ≈ 5000.

show abstract

Section: Cooling Subsystem Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic thermal and IT resource management strategies for data center energy minimization

Wan

Yang³

et al. 2017

J Cloud Comp

View full text Add to dashboard Cite

show abstract

“…The pressure drop over a rack consists of the pressure drop over the front doors, rear doors and over the servers [13]. …”

Section: ) Crah Pressure Dropmentioning

confidence: 99%

“…A limitation to this method is its complexity and high computational intensity. The energy consumption model of the different cooling system components was developed by Iyengar and Schmidt [5], [6]. They introduced a relationship between the flow rates of the CRAH units and the server racks Pelley et al published data center model included an idle consumption of the CRAH units [7].…”

Section: Introductionmentioning

confidence: 99%

Power Consumption Modeling of Data Center IT Room with Distributed Air Flow

Zhang¹,

Lindberg²,

Svensson³

et al. 2016

IJMO

View full text Add to dashboard Cite

 Abstract-Modern data centers are characterized by large sizes, high energy consumption and complexity involving IT, power supply, ventilation and cooling. Data center energy efficiency is a major concern for data center design and operation. To improve data center energy efficiency through efficient cooling and ventilation, advanced process control and optimization, process models to describe the process power consumption are required. In this work, data center power consumption models are investigated. A concept of distributed air flow control is presented. The objective is to develop a comprehensive data center power consumption model to describe IT room, computer room air handling (CRAH), data center ventilation and cooling characteristics as well as distributed air flow control. Data center operation scenarios with uneven IT load are simulated. Results show that the distributed air flow control can save the cooling energy significantly.

show abstract

“…The energy consumption of the cooling equipment is second only to that of the IT equipment. In response to this growing energy problem, all data centers have adopted new techniques to improve their energy efficiency [3], with most including accurate temperature control and air flow management of the air conditioning system [4][5][6]. In addition, 10% of data centers have air cooled or water cooled equipment which can use natural circulation to effectively cool the data center for free and thus reduce the energy consumption of the cooling equipment [7].…”

mentioning

confidence: 99%

Investigation into the energy consumption of a data center with a thermosyphon heat exchanger

Zhou

Tian

2011

Chin. Sci. Bull.

View full text Add to dashboard Cite

A data center test model was used to analyze the energy dissipation characteristics and energy consumption of a data center. The results indicate that adequate heat dissipation from a data center cannot be achieved only from heat dissipation through the building envelope during Beijing winter conditions. This is because heat dissipation through the building envelope covers about 19.5% of the total data center heat load. The average energy consumption for an air conditioner is 4 to 5 kW over a 24-h period. The temperature difference between the indoor and outdoor air for the data center with a thermosyphon heat exchanger is less than 20°C. The energy consumption of the thermosyphon heat exchanger is only 41% of that of an air conditioner. The annual energy consumption can be reduced by 35.4% with a thermosyphon system. In addition, the effect of the outdoor temperature on the energy consumption of an air conditioner is greater than the indoor room temperature. The energy consumption of an air conditioner system increases by 5% to 6% for every 1°C rise in the outdoor temperature. data center, energy consumption, thermosyphon heat exchanger, ambient energy Citation:Zhou F, Tian X, Ma G Y. Investigation into the energy consumption of a data center with a thermosyphon heat exchanger.

show abstract

Analytical Modeling for Thermodynamic Characterization of Data Center Cooling Systems

Cited by 49 publications

References 5 publications

Dynamic thermal and IT resource management strategies for data center energy minimization

Dynamic thermal and IT resource management strategies for data center energy minimization

Power Consumption Modeling of Data Center IT Room with Distributed Air Flow

Investigation into the energy consumption of a data center with a thermosyphon heat exchanger

Contact Info

Product

Resources

About