The Environmental Footprint of Data Centers

Author(s):  
Amip Shah ◽  
Cullen Bash ◽  
Ratnesh Sharma ◽  
Tom Christian ◽  
Brian J. Watson ◽  
...  

Numerous evaluation metrics and standards are being proposed across industry and government to measure and monitor the energy efficiency of data centers. However, the energy use of data centers is just one aspect of the environmental impact. In this paper, we explore the overall environmental footprint of data centers beyond just energy efficiency. Building upon established procedures from the environmental sciences, we create an end-to-end life-cycle model of the environmental footprint of data centers across a diverse range of impacts. We test this model in the case study of a hypothetical 2.2-MW data center. Our analysis suggests the need for evaluation metrics that go beyond just operational energy use in order to achieve sustainable data centers.

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Amip Shah ◽  
Cullen Bash ◽  
Ratnesh Sharma ◽  
Tom Christian ◽  
Brian J. Watson ◽  
...  

Numerous evaluation metrics and standards are being proposed across industry and government to measure and monitor the energy efficiency of data centers. However, the energy use of data centers is just one aspect of the environmental impact. In this paper, we explore the overall environmental footprint of data centers beyond just energy efficiency. Building upon established procedures from the environmental sciences, we create an end-to-end life-cycle model of the environmental footprint of data centers across a diverse range of impacts. We test this model in the case study of a hypothetical 2.2-MW data center. Our analysis suggests the need for evaluation metrics that go beyond just operational energy use in order to achieve sustainable data centers.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Muhammad Arif Budiyanto ◽  
Muhammad Hanzalah Huzaifi ◽  
Simon Juanda Sirait ◽  
Putu Hangga Nan Prayoga

AbstractSustainable development of container terminals is based on energy efficiency and reduction in CO2 emissions. This study estimated the energy consumption and CO2 emissions in container terminals according to their layouts. Energy consumption was calculated based on utility data as well as fuel and electricity consumptions for each container-handling equipment in the container terminal. CO2 emissions were estimated using movement modality based on the number of movements of and distance travelled by each container-handling equipment. A case study involving two types of container terminal layouts i.e. parallel and perpendicular layouts, was conducted. The contributions of each container-handling equipment to the energy consumption and CO2 emissions were estimated and evaluated using statistical analysis. The results of the case study indicated that on the CO2 emissions in parallel and perpendicular layouts were relatively similar (within the range of 16–19 kg/TEUs). These results indicate that both parallel and perpendicular layouts are suitable for future ports based on sustainable development. The results can also be used for future planning of operating patterns and layout selection in container terminals.


2021 ◽  
Vol 1 ◽  
pp. 3279-3288
Author(s):  
Maria Hein ◽  
Darren Anthony Jones ◽  
Claudia Margot Eckert

AbstractEnergy consumed in buildings is a main contributor to CO2 emissions, there is therefore a need to improve the energy performance of buildings, particularly commercial buildings whereby building service systems are often substantially over-designed due to the application of excess margins during the design process.The cooling system of an NHS Hospital was studied and modelled in order to identify if the system was overdesigned, and to quantify the oversizing impact on the system operational and embodied carbon footprints. Looking at the operational energy use and environmental performance of the current system as well as an alternative optimised system through appropriate modelling and calculation, the case study results indicate significant environmental impacts are caused by the oversizing of cooling system.The study also established that it is currently more difficult to obtain an estimate of the embodied carbon footprint of building service systems. It is therefore the responsibility of the machine builders to provide information and data relating to the embodied carbon of their products, which in the longer term, this is likely to become a standard industry requirement.


2021 ◽  
Vol 13 (11) ◽  
pp. 6114
Author(s):  
Matteo Manganelli ◽  
Alessandro Soldati ◽  
Luigi Martirano ◽  
Seeram Ramakrishna

Information and communication technologies (ICT) are increasingly permeating our daily life and we ever more commit our data to the cloud. Events like the COVID-19 pandemic put an exceptional burden upon ICT. This involves increasing implementation and use of data centers, which increased energy use and environmental impact. The scope of this work is to summarize the present situation on data centers as to environmental impact and opportunities for improvement. First, we introduce the topic, presenting estimated energy use and emissions. Then, we review proposed strategies for energy efficiency and conservation in data centers. Energy uses pertain to power distribution, ICT, and non-ICT equipment (e.g., cooling). Existing and prospected strategies and initiatives in these sectors are identified. Among key elements are innovative cooling techniques, natural resources, automation, low-power electronics, and equipment with extended thermal limits. Research perspectives are identified and estimates of improvement opportunities are mentioned. Finally, we present an overview on existing metrics, regulatory framework, and bodies concerned.


2018 ◽  
Vol 40 (2) ◽  
pp. 176-197
Author(s):  
S Hong ◽  
A Mylona ◽  
H Davies ◽  
P Ruyssevelt ◽  
D Mumovic

Accessing sufficient data for understanding how energy is used in non-domestic buildings is deemed to be a challenge in many countries. In the UK, such a challenge has led to limited understanding of long-term changes in energy use of buildings. This study aims to develop a deeper understanding of the trends in energy use across the public sector non-domestic buildings in England. Display energy certificate (DEC) data which relate to 59,740 public sector non-domestic buildings in England and Wales were analysed. Statistical analyses were carried out to understand both the latest patterns of energy use and how they have changed between 2010 and 2016. The patterns of energy use of various public-sector buildings were found to have gradually changed over the seven-year period. An imminent release of a revised dataset was deemed necessary for understanding the performance of buildings to support the aspirations set out in the clean growth strategy. The study pointed to a need for regularly gathering and sharing data for understanding the changes in the patterns of energy use of the stock. Developing a framework that can facilitate this would enable various stakeholders make informed decisions for improving energy efficiency of the UK’s non-domestic buildings. Practical application: Statistics on electrical and fossil-thermal energy use intensity provide up-to-date reference points for assessing operational energy efficiency of public sector buildings. Principles for developing a framework are provided to support various stakeholders make informed decisions on for example setting design targets or making capital investments.


2021 ◽  
Author(s):  
Ladan Vahidi-Arbabi

Thermal performance of complex buildings like data centers is not easy to evaluate. Experimental Investigation of the effects of energy conservation methods or any alteration that might occur in hundreds of variables in data centres would cost stakeholders time and money. And they might find worthless at times. Building energy model is a well-established field of science with an insufficient number of applications in data centers. This study presents methods of developing a data center model based on an actual case study. Moreover, it identifies effective calibrating strategies to increase the model performance accuracy relative to a recorded dataset. A reliable energy model can assist data center operators and researchers in different ways. As a result, calibrated energy model proved Earth Rangers’ data center can be independent of a heat pump or chiller use for most of the year, while ground heat exchangers deliver excessive heat to the ground as the heat sink.


Author(s):  
Milton Meckler

What does remain a growing concern for many users of Data Centers is their continuing availability following the explosive growth of internet services in recent years, The recent maximizing of Data Center IT virtualization investments has resulted in improving the consolidation of prior (under utilized) server and cabling resources resulting in higher overall facility utilization and IT capacity. It has also resulted in excessive levels of equipment heat release, e.g. high energy (i.e. blade type) servers and telecommunication equipment, that challenge central and distributed air conditioning systems delivering air via raised floor or overhead to rack mounted servers arranged in alternate facing cold and hot isles (in some cases reaching 30 kW/rack or 300 W/ft2) and returning via end of isle or separated room CRAC units, which are often found to fight each other, contributing to excessive energy use. Under those circumstances, hybrid, indirect liquid cooling facilities are often required to augment above referenced air conditioning systems in order to prevent overheating and degradation of mission critical IT equipment to maintain rack mounted subject rack mounted server equipment to continue to operate available within ASHRAE TC 9.9 prescribed task psychometric limits and IT manufacturers specifications, beyond which their operational reliability cannot be assured. Recent interest in new web-based software and secure cloud computing is expected to further accelerate the growth of Data Centers which according to a recent study, the estimated number of U.S. Data Centers in 2006 consumed approximately 61 billion kWh of electricity. Computer servers and supporting power infrastructure for the Internet are estimated to represent 1.5% of all electricity generated which along with aggregated IT and communications, including PC’s in current use have also been estimated to emit 2% of global carbon emissions. Therefore the projected eco-footprint of Data Centers into the future has now become a matter of growing concern. Accordingly our paper will focus on how best to improve the energy utilization of fossil fuels that are used to power Data Centers, the energy efficiency of related auxiliary cooling and power infrastructures, so as to reduce their eco-footprint and GHG emissions to sustainable levels as soon as possible. To this end, we plan to demonstrate significant comparative savings in annual energy use and reduction in associated annual GHG emissions by employing a on-site cogeneration system (in lieu of current reliance on remote electric power generation systems), introducing use of energy efficient outside air (OSA) desiccant assisted pre-conditioners to maintain either Class1, Class 2 and NEBS indoor air dew-points, as needed, when operated with modified existing (sensible only cooling and distributed air conditioning and chiller systems) thereby eliminating need for CRAC integral unit humidity controls while achieving a estimated 60 to 80% (virtualized) reduction in the number servers within a existing (hypothetical post-consolidation) 3.5 MW demand Data Center located in southeastern (and/or southern) U.S., coastal Puerto Rico, or Brazil characterized by three (3) representative microclimates ranging from moderate to high seasonal outside air (OSA) coincident design humidity and temperature.


Author(s):  
Abdlmonem H. Beitelmal ◽  
Drazen Fabris

New servers and data center metrics are introduced to facilitate proper evaluation of data centers power and cooling efficiency. These metrics will be used to help reduce the cost of operation and to provision data centers cooling resources. The most relevant variables for these metrics are identified and they are: the total facility power, the servers’ idle power, the average servers’ utilization, the cooling resources power and the total IT equipment power. These metrics can be used to characterize and classify servers and data centers performance and energy efficiency regardless of their size and location.


Author(s):  
Thomas J. Breen ◽  
Ed J. Walsh ◽  
Jeff Punch ◽  
Amip J. Shah ◽  
Niru Kumari ◽  
...  

As the energy footprint of data centers continues to increase, models that allow for “what-if” simulations of different data center design and management paradigms will be important. Prior work by the authors has described a multi-scale energy efficiency model that allows for evaluating the coefficient of performance of the data center ensemble (COPGrand), and demonstrated the utility of such a model for purposes of choosing operational set-points and evaluating design trade-offs. However, experimental validation of these models poses a challenge because of the complexity involved with tailoring such a model for implementation to legacy data centers, with shared infrastructure and limited control over IT workload. Further, test facilities with dummy heat loads or artificial racks in lieu of IT equipment generally have limited utility in validating end-to-end models owing to the inability of such loads to mimic phenomena such as fan scalability, etc. In this work, we describe the experimental analysis conducted in a special test chamber and data center facility. The chamber, focusing on system level effects, is loaded with an actual IT rack, and a compressor delivers chilled air to the chamber at a preset temperature. By varying the load in the IT rack as well as the air delivery parameters — such as flow rate, supply temperature, etc. — a setup which simulates the system level of a data center is created. Experimental tests within a live data center facility are also conducted where the operating conditions of the cooling infrastructure are monitored — such as fluid temperatures, flow rates, etc. — and can be analyzed to determine effects such as air flow recirculation, heat exchanger performance, etc. Using the experimental data a multi-scale model configuration emulating the data center can be defined. We compare the results from such experimental analysis to a multi-scale energy efficiency model of the data center, and discuss the accuracies as well as inaccuracies within such a model. Difficulties encountered in the experimental work are discussed. The paper concludes by discussing areas for improvement in such modeling and experimental evaluation. Further validation of the complete multi-scale data center energy model is planned.


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