A review on evaluation metrics of thermal performance in data centers

Gong, Xiao-Ming; Zhang, Zhongbin; Gan, Sixuan; Niu, Baolian; Yang, Libo; Xu, Haijin; Gao, Manfang

doi:10.1016/j.buildenv.2020.106907

Cited by 46 publications

(10 citation statements)

References 35 publications

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“…In the current literature, majority of the studies on green computing have focused on the development of frameworks for green computing technology (Ding et al , 2020), algorithms for green computing implementation (Rahmani et al , 2020), beliefs and personality traits of users (Dalvi-Esfahani et al , 2020) and evaluation metrics (Gong et al , 2020). With green computing being an emerging technological paradigm, it would be useful to analyze its characteristics in parallel with other innovations which already have well-established analytical frameworks.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel hybrid DEMATEL-K-means clustering algorithm for modeling the barriers of green computing adoption in the Philippines

Abellana

Mayol

2021

JM2

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Purpose This paper aims to propose a novel hybrid-decision-making trial and evaluation laboratory-K means clustering algorithm as a decision-making framework for analyzing the barriers of green computing adoption. Design/methodology/approach A literature review is conducted to extract relevant green computing barriers. An expert elicitation process is performed to finalize the barriers and to establish their corresponding interrelationships. Findings The proposed approach offers a comprehensive framework for modeling the barriers of green computing adoption. Research limitations/implications The results of this paper provide insights on how the barriers of green computing adoption facilitate the adoption of stakeholders. Moreover, the paper provides a framework for analyzing the structural relationships that exist between factors in a tractable manner. Originality/value The paper is one of the very first attempts to analyze the barriers of green computing adoption. Furthermore, it is the first to offer lenses in a Philippine perspective. The paper offers a novel algorithm that can be useful in modeling the barriers of innovation, particularly, in green computing adoption.

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Section: Literature Reviewmentioning

confidence: 99%

A novel hybrid DEMATEL-K-means clustering algorithm for modeling the barriers of green computing adoption in the Philippines

Abellana

Mayol

2021

JM2

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“…We reviewed the existing metrics that describe air distribution in data centers [32], such as the Rack Cooling Index (RCI) and Return Temperature Index (RTI) introduced by Herrlin [33,34], Air Distribution Index (ADI) and Air Mixing Index (AMI) proposed by Qian et al [35], Air Distribution Effectiveness (ADE) proposed by Zhang et al [36], and negative pressure ratio, bypass ratio, recirculation ratio, etc., proposed by Tozer et al [37]. The RCI and RTI metrics work well to evaluate the air management effectiveness of data centers, but are not suitable for energy simulation.…”

Section: Supply and Return Approach Temperaturesmentioning

confidence: 99%

Prototype energy models for data centers

Sun

Luo

et al. 2021

Energy and Buildings

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Data centers in the United States consume about two percent of the nation's electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy's Commercial Prototype Building Models. This study presented the development of two new data center prototype models and their implementation in OpenStudio and EnergyPlus. The small-size data center model represents a computer room in a building served by computer room air conditioners (CRACs); while the large-sized model represents stand-alone data centers served by computer room air handlers (CRAHs) with a central chiller plant. For each data center model, two levels of IT equipment (ITE) load density were considered, to cover the wide range of IT power density of data centers: 40 and 100 W/ft 2 (430 and 1,076 W/m 2) for the computer room, and 100 and 500 W/ft 2 (1,076 and 5,382 W/m 2) for the standalone data center. All other assumptions, such as building envelope, lighting, HVAC efficiencies and schedules, were based on the minimal requirements of ASHRAE Standard 90.1 at various vintages. We introduced a novel concept of supply and return air approach temperatures to capture the essential effects of non-uniform airflow and temperature distribution in data centers. The approach temperatures were pre-computed by computational fluid dynamics (CFD) simulations for various configurations of ITE loads and airflow containment management in data centers. A new feature was developed in EnergyPlus to implement the approach temperature method. A case study was conducted to demonstrate the use of the data center models. The two data center models cover all U.S. climate zones and can be used to evaluate energy saving measures for data centers, as well as to support development of data center energy efficiency codes and standards.

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“…Due to its characteristics of high reliability, low initial investment and maintenance costs, air-side cooling technologies have been widely used and regarded as a preferred cooling scheme in DCs in the past several decades [9]. Therefore, typical DCs generally adopt traditional air-cooled refrigeration technology (e.g., traditional computer room air conditioning (CRAC) units comprised of coolers, water pumps, and cooling towers) [10]. Although air-side cooling systems have been widely used in DCs, they have low cooling efficiency, which results in energy waste and system operation risk of over-heating.…”

Section: Introductionmentioning

confidence: 99%

Design and Thermal Environment Analysis of a Decentralized Cooling System with Surface-Mount Heat Pipe Exchangers on Servers in Data Centers

et al. 2022

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This paper proposes a decentralized cooling system combined with a traditional computer room air conditioning unit and server-level heat pipe exchangers for thermal environment optimization in a data center. Two cooling strategies, with heat exchangers installed above and below the servers respectively, are proposed and compared with the original CRACs system in terms of thermal environment. The simulation results of the original data center model are in good agreement with the on-site measurement results, and thus its reliability can be validated. The results show that a decentralized cooling system can effectively improve the thermal environment in data centers. To obtain the highest cooling efficiency, altogether 18 cases, where heat pipe exchangers were installed at different locations and heights, are analyzed and compared. The results show that the thermal environment is optimal when heat pipe exchangers are installed 0.01 m below each server. The local hotspot temperature is reduced by 6.8 °C, and the temperature distribution of the rack is the most uniform, which can effectively reduce the heat accumulation in data centers.

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A review on evaluation metrics of thermal performance in data centers

Cited by 46 publications

References 35 publications

A novel hybrid DEMATEL-K-means clustering algorithm for modeling the barriers of green computing adoption in the Philippines

A novel hybrid DEMATEL-K-means clustering algorithm for modeling the barriers of green computing adoption in the Philippines

Prototype energy models for data centers

Design and Thermal Environment Analysis of a Decentralized Cooling System with Surface-Mount Heat Pipe Exchangers on Servers in Data Centers

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