Addressing Thermal Challenges in Design of Data Centres

2010 ◽  
Author(s):  
Babak Fakhim ◽  
Srinarayana Nagarathinam ◽  
Simon Wong ◽  
Masud Behnia ◽  
Steve Armfield
Keyword(s):  
Energy Consumption ◽  
Hot Spots ◽  
Heat Dissipation ◽  
Field Measurements ◽  
Temperature Fields ◽  
Power Requirement ◽  
Data Centre ◽  
It Systems ◽  
Improved Design ◽  
Data Centres

Aggregation of small networking hardware has led to an ever increasing power density in data centres. The energy consumption of IT systems is continuing to rise substantially owing to the demands of electronic information and storage requirements. Energy consumption of data centres can be severely and unnecessarily high due to inadequate localised cooling and densely packed rack layouts. However, as heat dissipation in data centres rises by orders of magnitude, inefficiencies such as air recirculation causing hot spots, leading to flow short-circuiting will have a significant impact on the thermal manageability and energy efficiency of the cooling infrastructure. Therefore, the thermal management of high-powered electronic components is a significant challenge for cooling of data centres. In this project, an operational data centre has been studied. Field measurements of temperature have been performed. Numerical analysis of flow and temperature fields is conducted in order to evaluate the thermal behaviour of the data centre. A number of undesirable hot spots have been identified. To rectify the problem, a few practical design solutions to improve the cooling effectiveness have been proposed and examined to ensure a reduced air-conditioning power requirement. Therefore, a better understanding of the cooling issues and the respective proposed solutions can lead to an improved design for future data centres.

An Energy-Aware Real-Time VM-Provisioning Framework For Heterogeneous Data Centres

2021 ◽  
Author(s):  
Salam Ismaeel
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Power Efficiency ◽  
Large Scale ◽  
Virtual Machines ◽  
Heterogeneous Data ◽  
Energy Aware ◽  
Time Dynamic ◽  
Data Centre ◽  
Data Centres

<div>Increasing power efficiency is one of the most important operational factors for any data centre providers. In this context, one of the most useful approaches is to reduce the number of utilized Physical Machines (PMs) through optimal distribution and re-allocation of Virtual Machines (VMs) without affecting the Quality of Service (QoS). Dynamic VMs provisioning makes use of monitoring tools, historical data, prediction techniques, as well as placement algorithms to improve VMs allocation and migration. Consequently, the efficiency of the data centre energy consumption increases.</div><div>In this thesis, we propose an efficient real-time dynamic provisioning framework to reduce energy in heterogeneous data centres. This framework consists of an efficient workload preprocessing, systematic VMs clustering, a multivariate prediction, and an optimal Virtual Machine Placement (VMP) algorithm. Additionally, it takes into consideration VM and user behaviours along with the existing state of PMs. The proposed framework consists of a pipeline successive subsystems. These subsystems could be used separately or combined to improve accuracy, efficiency, and speed of workload clustering, prediction and provisioning purposes.<br></div><div>The pre-processing and clustering subsystems uses current state and historical workload data to create efficient VMs clusters. Efficient VMs clustering include less consumption resources, faster computing and improved accuracy. A modified multivariate Extreme Learning Machine (ELM)-based predictor is used to forecast the number of VMs in each cluster for the subsequent period. The prediction subsystem takes users’ behaviour into consideration to exclude unpredictable VMs requests.<br></div><div>The placement subsystem is a multi-objective placement algorithm based on a novel Machine Condition Index (MCI). MCI represents a group of weighted components that is inclusive of data centre network, PMs, storage, power system and facilities used in any data centre. In this study it will be used to measure the extent to which PM is deemed suitable for handling the new and/or consolidated VM in large scale heterogeneous data centres. It is an efficient tool for comparing server energy consumption used to augment the efficiency and manageability of data centre resources.</div><div> The proposed framework components separately are tested and evaluated with both synthetic and realistic data traces. Simulation results show that proposed subsystems can achieve efficient results as compared to existing algorithms. <br></div>

Greener Data Centres in the Netherlands

2011 ◽  
pp. 91-109
Author(s):  
Theo Thiadens ◽  
Marko Dorenbos ◽  
Andries Kasper ◽  
Anda Counoutte-Potman
Keyword(s):  
Energy Consumption ◽  
The Netherlands ◽  
Current Situation ◽  
Dutch Government ◽  
Data Centre ◽  
Data Centres

The conclusion of this chapter is that in the year 2009, the norms in this field are not yet fully present; that by making use of these norms in procurement, buyers will be able to arrive at more sustainable ICT; that from the current situation, consolidation alone could without any problem, enable achievement of the long-term agreement between the Dutch ICT trade organization and the Dutch government, an agreement in which over a period of 25 years starting in 2005, 2% less energy should be used every year; that every data centre needs to map its energy consumption and sustainability systematically, and that in 2009, over 50% over the annually installed ICT equipment in the Netherlands is recycled.

scholarly journals Design Improvement of Water-Cooled Data Centres Using Computational Fluid Dynamics

2021 ◽  
pp. 105-113
Author(s):  
Ramamoorthy Sethuramalingam ◽  
Abhishek Asthana
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Energy Consumption ◽  
Heat Exchanger ◽  
Alternative Energy ◽  
Early Developmental Stage ◽  
Cfd Modelling ◽  
Data Centre ◽  
Liquid Heat ◽  
Data Centres

AbstractData centres are complex energy demanding environments. The number of data centres and thereby their energy consumption around the world is growing at a rapid rate. Cooling the servers in the form of air conditioning forms a major part of the total energy consumption in data centres and thus there is an urgent need to develop alternative energy efficient cooling technologies. Liquid cooling systems are one such solution which are in their early developmental stage. In this article, the use of Computational Fluid Dynamics (CFD) to further improve the design of liquid-cooled systems is discussed by predicting temperature distribution and heat exchanger performance. A typical 40 kW rack cabinet with rear door fans and an intermediate air–liquid heat exchanger is used in the CFD simulations. Steady state Reynolds-Averaged Navier–Stokes modelling approach with the RNG K-epsilon turbulence model and the Radiator boundary conditions were used in the simulations. Results predict that heat exchanger effectiveness and uniform airflow across the cabinet are key factors to achieve efficient cooling and to avoid hot spots. The fundamental advantages and limitations of CFD modelling in liquid-cooled data centre racks were also discussed. In additional, emerging technologies for data centre cooling have also been discussed.

An Energy-Aware Real-Time VM-Provisioning Framework For Heterogeneous Data Centres

2021 ◽  
Author(s):  
Salam Ismaeel
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Power Efficiency ◽  
Large Scale ◽  
Virtual Machines ◽  
Heterogeneous Data ◽  
Energy Aware ◽  
Time Dynamic ◽  
Data Centre ◽  
Data Centres

<div>Increasing power efficiency is one of the most important operational factors for any data centre providers. In this context, one of the most useful approaches is to reduce the number of utilized Physical Machines (PMs) through optimal distribution and re-allocation of Virtual Machines (VMs) without affecting the Quality of Service (QoS). Dynamic VMs provisioning makes use of monitoring tools, historical data, prediction techniques, as well as placement algorithms to improve VMs allocation and migration. Consequently, the efficiency of the data centre energy consumption increases.</div><div>In this thesis, we propose an efficient real-time dynamic provisioning framework to reduce energy in heterogeneous data centres. This framework consists of an efficient workload preprocessing, systematic VMs clustering, a multivariate prediction, and an optimal Virtual Machine Placement (VMP) algorithm. Additionally, it takes into consideration VM and user behaviours along with the existing state of PMs. The proposed framework consists of a pipeline successive subsystems. These subsystems could be used separately or combined to improve accuracy, efficiency, and speed of workload clustering, prediction and provisioning purposes.<br></div><div>The pre-processing and clustering subsystems uses current state and historical workload data to create efficient VMs clusters. Efficient VMs clustering include less consumption resources, faster computing and improved accuracy. A modified multivariate Extreme Learning Machine (ELM)-based predictor is used to forecast the number of VMs in each cluster for the subsequent period. The prediction subsystem takes users’ behaviour into consideration to exclude unpredictable VMs requests.<br></div><div>The placement subsystem is a multi-objective placement algorithm based on a novel Machine Condition Index (MCI). MCI represents a group of weighted components that is inclusive of data centre network, PMs, storage, power system and facilities used in any data centre. In this study it will be used to measure the extent to which PM is deemed suitable for handling the new and/or consolidated VM in large scale heterogeneous data centres. It is an efficient tool for comparing server energy consumption used to augment the efficiency and manageability of data centre resources.</div><div> The proposed framework components separately are tested and evaluated with both synthetic and realistic data traces. Simulation results show that proposed subsystems can achieve efficient results as compared to existing algorithms. <br></div>

Towards Energy Efficiency for Cloud Computing Services

2013 ◽  
pp. 306-328
Author(s):  
Daniele Tafani ◽  
Burak Kantarci ◽  
Hussein T. Mouftah ◽  
Conor McArdle ◽  
Liam P. Barry
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Green Technologies ◽  
Core Networks ◽  
Data Centre ◽  
Computing Services ◽  
Efficient Data ◽  
Cloud Computing Services ◽  
Data Centres

Over the past decade, the increasing complexity of data-intensive cloud computing services along with the exponential growth of their demands in terms of computational resources and communication bandwidth presented significant challenges to be addressed by the scientific research community. Relevant concerns have specifically arisen for the massive amount of energy necessary for operating, connecting, and maintaining the thousands of data centres supporting cloud computing services, as well as for their drastic impact on the environment in terms of increased carbon footprint. This chapter provides a survey of the most popular energy-conservation and “green” technologies that can be applied at data centre and network level in order to overcome these issues. After introducing the reader to the general problem of energy consumption in cloud computing services, the authors illustrate the state-of-the-art strategies for the development of energy-efficient data centres; specifically, they discuss principles and best practices for energy-efficient data centre design focusing on hardware, power supply specifications, and cooling infrastructure. The authors further consider the problem from the perspective of the network energy consumption, analysing several approaches achieving power efficiency for access, and core networks. Additionally, they provide an insight to recent development in energy-efficient virtual machine placement and dynamic load balancing. Finally, the authors conclude the chapter by providing the reader with a novel research work for the establishment of energy-efficient lightpaths in computational grids.

Pseudo Dry Gas Technology: Pathway to Decarbonisation of Energy Consumption for Remote Offshore Gas Fields

2021 ◽  
Author(s):  
Tran Nguyet Ngo ◽  
Lee Thomas ◽  
Kavitha Raghavendra ◽  
Terry Wood
Keyword(s):  
Energy Consumption ◽  
Energy Transition ◽  
High Energy ◽  
Innovative Technology ◽  
Flow Loop ◽  
Gas Field ◽  
Power Requirement ◽  
Order Of Magnitude ◽  
Gas Fields ◽  
Technology Pathway

Abstract Transporting large volumes of gas over long distances from further and deeper waters remains a significant challenge in making remote offshore gas field developments technologically and economically viable. The conventional development options include subsea compression, floating topside with topside compression and pipeline tie-back to shore, or floating liquefied natural gas vessels. However, these options are CAPEX and OPEX intensive and require high energy consumption. Demand for a lower emission solution is increasingly seen as the growing trend of global energy transition. Pseudo Dry Gas (PDG) technology is being developed by Intecsea, Worley Group and The Oil & Gas Technology Centre (Aberdeen) and tested in collaboration with Cranfield University. This is applied to develop stranded or remote gas reserves by removing fluids at the earliest point of accumulation at multiple locations, resulting in near dry gas performance. This technology aims to solve liquid management issues and subsequently allows for energy efficient transportation of the subsea gas enabling dramatic reductions in emissions. The PDG prototype tested using the Flow Loop facilities at Cranfield University has demonstrated the concept’s feasibility. Due to a greater amount of gas recovered with a much lower power requirement, the CO2 emissions per ton of gas produced via the PDG concept is by an order of magnitude lower than conventional methods. This study showed a reduction of 65% to 80% against standard and alternative near future development options. The paper considers innovative technology and a value proposition for the Pseudo Dry Gas concept based on a benchmarked study of a remote offshore gas field. The basin was located in 2000m of water depth, with a 200km long subsea tie-back. To date the longest tieback studied was 350km. It focused on energy consumption and carbon emission aspects. The conclusion is that decarbonisation of energy consumption is technically possible and can be deployed subsea to help meet this future challenge and push the envelope of subsea gas tie-backs.

Cleaner, greener data centres

ITNOW ◽  
2021 ◽  
Vol 63 (4) ◽  
pp. 18-20
Author(s):  
John Booth
Keyword(s):  
Climate Change ◽  
Energy Efficiency ◽  
Energy Use ◽  
Data Centre ◽  
Eu Directives ◽  
Data Centres

Abstract John Booth MBCS, Data Centre Energy Efficiency and Sustainability Consultant at Carbon3IT, explores the detrimental trajectory of data centre energy use, against a backdrop of COP26, climate change and proposed EU directives.

Numerical Study on Flow Characteristics in High Multi-Stage Pressure Reducing Valve

2017 ◽  
Author(s):  
Fu-qiang Chen ◽  
Zhi-xin Gao ◽  
Jin-yuan Qian ◽  
Zhi-jiang Jin
Keyword(s):  
Energy Consumption ◽  
Numerical Study ◽  
Research Work ◽  
Flow Characteristics ◽  
Temperature Fields ◽  
Turbulent Dissipation ◽  
Technological Support ◽  
Multi Stage ◽  
Valve Opening ◽  
Pressure Reducing Valve

In this paper, a new high multi-stage pressure reducing valve (HMSPRV) is proposed. The main advantages include reducing noise and vibration, reducing energy consumption and dealing with complex conditions. As a new high pressure reducing valve, its flow characteristics need to be investigated. For that the valve opening has a great effect on steam flow, pressure reduction and energy consumption, thus different valve openings are taken as the research points to investigate the flow characteristics. The analysis is conducted from four aspects: pressure, velocity, temperature fields and energy consumption. The results show that valve opening has a great effect on flow characteristics. No matter for pressure, velocity or temperature field, the changing gradient mainly reflects at those throttling components for all valve openings. For energy consumption, in the study of turbulent dissipation rate, it can be found that the larger of valve opening, the larger of energy consumption. It can be concluded that the new high multi-stage pressure reducing valve works well under complex conditions. This study can provide technological support for achieving pressure regulation, and benefit the further research work on energy saving and multi-stage design of pressure reducing devices.

scholarly journals Trends in Data Centre Energy Consumption under the European Code of Conduct for Data Centre Energy Efficiency

Energies ◽  
2017 ◽  
Vol 10 (10) ◽  
pp. 1470 ◽  
Author(s):  
Maria Avgerinou ◽  
Paolo Bertoldi ◽  
Luca Castellazzi
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Code Of Conduct ◽  
Data Centre ◽  
European Code

Study and Simulation on the Energy Efficiency Management Control Strategy of Ship Based on Clean Propulsion System

2015 ◽  
Author(s):  
Kai Wang ◽  
Xinping Yan ◽  
Yupeng Yuan
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Control Strategy ◽  
Control Strategies ◽  
Management Control ◽  
Propulsion System ◽  
Power Requirement ◽  
Doubly Fed ◽  
System Configurations ◽  
And Control

Nowadays, with the higher voice of ship energy saving and emission reduction, the research on energy efficiency management is particularly necessary. Energy efficiency management and control of ships is an effective way to improve the ship energy efficiency. In this paper, according to the new clean propulsion system configurations of 5000 tons of bulk carrier, the energy efficiency management control strategy of the clean propulsion system is designed based on the model of advanced brushless doubly-fed shaft generator, propulsion system using LNG/diesel dual fuel engine and energy consumption of the main engine for reducing energy consumption. The simulation model of the entire propulsion system and the designed control strategy were designed. The influence of the engine speed on the ship energy efficiency was analyzed, and the feasibility of the energy efficiency management control strategies was verified by simulation using Matlab/Simulink. The results show that the designed strategies can ensure the power requirement of the whole ship under different conditions and improve the ship energy efficiency and reduce CO2 emissions.

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