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Abstract Due to their significant internal heat gain resulting from computer server banks, data centres require cooling year-round, creating an opportunity to transport the waste heat to heat-deficient neighbouring buildings. This paper evaluates the quantity of multi-unit residential buildings (MURBs) that should be connected to a given data centre in order to maximize the portion of shared energy which provides the MURBs' heating energy and the data centre's cooling energy simultaneously. The paper then evaluates the financial viability and greenhouse gas (GHG) emissions of three different methods with which energy can be shared from a data centre to surrounding MURBs in a community energy network (CEN). The first method, called the Energy Sharing System involves using a heat pump to produce heating and cooling at the same time for the MURBs and the data centre. The second, called the One-Borefield System, has the same energy sharing aspect as the first, with additional heating and cooling coming from geo-exchange. The third method, called the Two-Borefield System, is an innovative approach to geo-exchange, which uses two separate borefields to achieve free cooling, while also incorporating the energy sharing base. The investigation finds that the optimal MURB area that should be connected to a 4000 kW cooling load data centre is 110,000 m2 for the Toronto (Canada) climate. The financial analysis shows that the Energy Sharing System was the most profitable, with a 11.9% 30-year unlevered after-tax internal rate of return (IRR). [ABSTRACT FROM AUTHOR]

• An innovative dew point cooling system was designed, constructed, installed and real live tested in live data centre. • The system can provide continuously stable cooling air and maintain the required temperature and humidity in data centre. • The average COP of 29.7 was achieved during the testing period. • 90 % energy saving can be achieved for data centre cooling. • Suitability, stability and reliability of the system used in data centre environment were proved. This paper presents the development and application of a super performance dew point cooling technology for data centres. The novel super performance dew point cooler showed considerably improved energy saving and carbon reduction for data centre cooling. The innovations of this technology are built upon a series of technological breakthroughs including, a novel hybrid flat/corrugated heat and mass exchanging sheets, an innovative highly water absorptive and diffusive wet-material for the sheets which enable an intermittent water supply with well-tuned water pressure and flow rate, and the optimised fan configurations. Following a list of fundamental research including theoretical, numerical and lab experimental testing of a small scale prototype system, a specialist 100 kW rated data centre dew point cooling system was dedicated designed, constructed, installed and real life tested in an operational live data centre environment, i.e., Maritime Data Centre at Hull (UK) to investigate its dynamic performance, suitability and stability for application in operational data centre environment conditions. During the testing period, the system showed its reliability and capability to remove a tremendous amount of heat dissipated from the IT equipment and maintain an adequate space temperature in the operational live data centre. The dynamic data collection and analysis during the continuous testing and monitoring period showed the average COP of 29.7 with the maximum COP of 48.3. Compared to the existing traditional vapor compression air conditioning system in the data centre, the energy saving using the super performance dew point cooling system is around 90 %. The work presented in this paper include detailed innovation aspects of the technology and the system operation, as well as the established bridging knowledges, methodology and technical procedure for bringing this new technology into real life operation which involve in data centre survey, optimum design and modularization of the specialist cooling system for data centre application, proven system installation, operating method and cooling air management for data centre as well as the assurance of the continuous sufficient cooling supply to the data centre. [ABSTRACT FROM AUTHOR]

At present, cooling of data centres efficiently is proving a challenging feat for many companies. With constantly increasing server size and IT demand, combined with the ever increasing energy consciousness of the world, many cooling systems are no longer up to the task of effectively cooling these Data Centres while maintaining an energy efficient environment. A review of journal papers, white papers, and information from companies who manufacture data centre cooling solutions was undertaken. The literature reviewed shows that any solution to this increasing problem needs to be flexible. Investigation was carried out on two different types of cooling system which showed the most promise within the literature review. An air-cooled type (hot aisle containment air cooling) and a liquid-cooled type (single-phase liquid immersion cooling) were the two types of data centre cooling systems selected. 2D simulation of each of these systems, using ANSYS © Fluent 17.2 Academic, was carried out to demonstrate the flexibility of each system when rack density is increased from 15kW to 30kW. Conclusions were drawn that air was not a flexible cooling method if changes were to be made to the IT equipment, with a maximum outlet temperature of 324K (51°C) for the 15kW system rising to 342K (69°C) when changed to a 30kW system. It was also found that liquid immersion cooling was flexible and maintained an average outlet temperature of 298K (25°C) even when the IT equipment was uprated to 30kW. [ABSTRACT FROM AUTHOR]

The design of a complex power supply infrastructure and the satisfaction of the concentrated high energy demand is a constant challenge for data centre owners. Furthermore, economics of the operation and ideas of sustainability are getting more and more attention lately as well. Green data centres are designed to minimize the effect on the natural environment. One of the primary goals of such units is to decrease the energy needs both for the computing infrastructure and the supporting systems (e.g. thermal management), which can be achieved either by increasing the efficiency of processes or by integrating renewable energy sources. Present paper introduces results of an ongoing research and development cooperation between the Centre for Energy Research of the Hungarian Academy of Sciences and Persecutor Ltd., supported by the Hungarian Government’s “PIAC_13” programme. The project aims to develop a new, highly energy efficient data centre infrastructure, which is able to supply IT needs at a high-level, while minimizing power losses. Present paper focuses on decreasing power losses in the distribution and power conversion infrastructure. A power loss model, capable of supporting the optimal selection of different subsystems of the technological chain, is introduced and two case studies are shown to demonstrate the effect of different loss reduction options. [ABSTRACT FROM AUTHOR]

Energy efficiency is a critical issue in data centre management, which is the foundation for cloud computing. The VM placement has a considerable impact on a data centre's energy efficiency and resource utilisation. The assignment of VMs to PMs is an NP-hard problem without an easy way to find an optimal solution, particularly in large-scale data centres. In this study, the VM placement problem is formulated as a constrained optimisation problem. The Genetic Algorithm (GA) is a suitable method for solving this problem in terms of the quality of the solution. However, GA is time-consuming to obtain an optimal solution in the large scale optimisation problem. Therefore, this paper focuses on accelerated GA for energy-efficient VM placement. As the most time-consuming element of the GA is the calculation of its fitness function, this paper simplifies this calculation through a new fitness function in GA. Simulation results of small-, medium-, and large-scale data centres demonstrate that our accelerated GA is faster than the standard GA and gives better quality of solution than the First Fit Decreasing (FFD) algorithm, respectively. The findings of our GA with the new fitness function reveal an 8% energy saving for our GA compared to FFD and a 66% reduction in our GA execution time compared to the standard GA with standard energy formula as a fitness function. The number of generations in our GA is reduced by about 50% in comparison with the standard GA. Moreover, we started with 3000 PMs in the large-scale dataset, and only 1086 PMs were actually used after running our GA. Therefore, we may switch off far more PMs for energy savings from our GA results than those from the standard GA. • Virtual machine placement problem formulated as a constrained optimisation problem. •It focuses on accelerated genetic algorithm for virtual machine placement. •Our algorithm can minimise residual resources using Taylor extension. •Our solution quality is better than FFD and standard genetic algorithm. •It reduces execution time and energy in large scale data centres. [ABSTRACT FROM AUTHOR]

Abstract With the advent of high-performance of data centre, the energy consumption of servers has proliferated. Consequently, the generated tremendous amount of heat requires huge energy consumption. Improving energy efficiency is going to play a key role in reducing the energy consumption of data centre. Adopting the heat sink with higher heat transfer and flow performance or precisely control the cooling capacity are two effective way for energy saving in heat dissipation. In this paper, three water cooled heat sink with different pin fin are evaluated by experiments. The heat sink with square pin fin has better heat and flow effect. Meanwhile, the precisely control of the pump power according to the working load is used for energy saving. The energy saving effect is evaluated by benefit factor. However, the most effective way of energy saving is adopting the heat sink with higher comprehensive effect. [ABSTRACT FROM AUTHOR]

The Neutrino Platform (NP) is the CERN venture to foster and support the next generation of accelerator-based neutrino oscillation experiments. Part of the present CERN Medium-Term Plan, the NP provides facilities to develop and prototype the next generation of neutrino detectors while contributing to unify the European neutrino community towards the US and Japanese projects. A significative effort is made on R&D for LAr TPC technologies: two big LAr TPC prototypes for the DUNE far detector are under construction at CERN. Those detectors will be exposed in summer 2018 to an entirely new and NP-dedicated beam-line from the SPS which will provide electron, muon and hadron beams with energies in the range of sub-GeV to a few GeV. The total raw data volume that is slated to be collected during the scheduled 3-month beam run is estimated to be in excess of 2.5 PB for each detector. In this paper, the current status of NP Computing Infrastructure approach is presented to solving these problems by leveraging the design, expertise and components into a unified architecture that is capable of meeting the needs of NP prototypes experiments. [ABSTRACT FROM AUTHOR]

The total energy demand of data centres has experienced an important increase in the last years. This is why data centres industry and researchers are working on implementing energy efficiency measures in data centre portfolio. The cooling system of these unique infrastructures can account for 40% of the total energy consumption. Therefore, air management plays an important role to reduce operating costs and to increase overall cooling system efficiency. In order to improve and optimize the energy consumption and thermal management in data centres, appropriate metrics are imperative to evaluate their efficiency and performance. The present paper examines the air management of a real data centre by the use of the most promising air metrics. Noticeable air recirculation and hot spots were observed in the facility. Dynamic modelling was used to evaluate the benefit of air inefficiency mitigation. The combination of air management improvement with increasing the supply air temperature and reducing the air flow rate would allow important energy reduction in the cooling system. [ABSTRACT FROM AUTHOR]

The energy use of data centres is increasing as the data storage needs increase. One of the largest items in the energy use of these facilities is cooling. A fuel cell-based combined cooling, heating and power system can efficiently meet such a centre's need for cooling and in the meantime generate enough electricity for the centre and more. In this paper the economic feasibility of a fuel cell-based combined cooling, heating and power system that meets the energy demands of such a facility is investigated using operational data from an existing data centre in Stockholm, Sweden. The results show that although the system is not feasible with current energy prices and technology it may be feasible in the future with the projected changes in energy prices. [ABSTRACT FROM AUTHOR]

Electricity consumption typically forms the biggest portion of a Data Centre's operational cost, with the biggest consumers, in roughly equal proportion, being the servers and the cooling units. In an effort to reduce electricity consumption, in this paper, we propose a grid scheduling algorithm that takes advantage of a prior Gas-District Cooling Data Centre model to reduce the cooling energy consumption. The scheduling algorithm is an extension of a prior version that has been shown to perform with competitive average turnaround time, waiting time and maximum tardiness in heterogeneous grid environments. Experimental analysis shows that the proposed method was able to reduce cooling electricity consumption by 20%. Further, by increasing the maximum allowable temperature by 1 degree, the proposed method was able to save an additional 3%. [ABSTRACT FROM AUTHOR]

The ever-increasing density in cloud computing parties, i.e. users, services, providers and data centres, has led to a significant exponential growth in: data produced and transferred among the cloud computing parties; network traffic; and the energy consumed by the cloud computing massive infrastructure, which is required to respond quickly and effectively to users requests. Transferring big data volume among the aforementioned parties requires a high bandwidth connection, which consumes larger amounts of energy than just processing and storing big data on cloud data centres, and hence producing high carbon dioxide emissions. This power consumption is highly significant when transferring big data into a data centre located relatively far from the users geographical location. Thus, it became high-necessity to locate the lowest energy consumption route between the user and the designated data centre, while making sure the users requirements, e.g. response time, are met. The main contribution of this paper is GreeDi, a network-based routing algorithm to find the most energy efficient path to the cloud data centre for processing and storing big data. The algorithm is, first, formalised by the situation calculus. The linear, goal and dynamic programming approaches are used to model the algorithm. The algorithm is then evaluated against the baseline shortest path algorithm with minimum number of nodes traversed, using a real Italian ISP physical network topology. [ABSTRACT FROM AUTHOR]

Heat pipe, a high efficient, cost effective and reliable device, is considered one of the most promising passive technologies for cooling data centres. Aiming to provide comprehensive information and focused perspective on heat pipe system for cooling data centres, the literature reviewed in this review is obtained from the Web of Science by searching the topic "heat pipe" and "data centre" conducted on Sep. 1, 2019 for the decade from 2009 to 2018. In this paper, a comprehensive review on heat pipes for use in data centre cooling systems will be carried out, starting from the working principle, heat transfer analysis and applications. The review works will be analysed in terms of the system research methodology, energy performance evaluation, and IT tasks. From the system research methodology, the heat pipe structure, simulation and testing analyses were conducted. From the energy performance evaluation, the energy consumption, energy recovery and energy saving analyses were studied. From the IT tasks, the avoidance of hot spots and thermal management in the data centres were analysed. The opportunities for further works are revealed including: developing new and efficient data centre cooling systems employing advanced technology; optimising the heat pipe structure for the data centre cooling systems; testing the data centre cooling systems under actual conditions; and evaluating the economic feasibility and market potential of the data centre cooling systems. This review provides the guidelines for the development of data centre cooling system based on the heat pipe. • The heat pipe systems for cooling data centres are summarized from the research methodology, energy performance evaluation, and IT tasks. • Opportunities of data center cooling system based on the heat pipe are emphasized. • The evaluation of economic feasibility and market potential of the data centre cooling systems based heat pipe is needed. • Further tests of the data centre cooling systems in real environment should be carried out. [ABSTRACT FROM AUTHOR]

The massive data centre energy consumption has motivated significant efforts to use energy efficiency strategies and the implementation of renewable energy sources that reduce their operational costs and environmental impact. Considering that the potential of many of these measures is often closely linked to the climate conditions, the location of data centres can have a major impact on their energy demand. Moreover, from a holistic approach, differences among regions become even more important when accounting for the electricity attributes from the grid. To assess these differences this work compares by the use of energy indicators the behaviour of a data centre located at different representative emplacements in Europe. To do so, a dynamic energy model which incorporates free cooling strategy and photovoltaic energy is developed. The paper concludes by suggesting that future data centre developments could consider site selection as a new strategy to limit the environmental impact attributable to this sector. [ABSTRACT FROM AUTHOR]

The continuous growth in size, complexity and energy density of data centres due to the increasing demand for storage, networking and computation has become a worldwide energetic problem. The emergent awareness of the negative impact that the uncontrolled energy consumption has on natural environment, the predicted limitation of fossil fuels production in the upcoming decades and the growing associated costs have strongly influenced the energy systems engineering work in the last decades. Therefore, the implementation of well known and advanced energy efficiency measures to reduce data centres energy demand play an important role not only to a supportable growth but also to reduce its operational costs. The carbon footprint is greatly influenced by the energy sources used. Therefore, there have been recent efforts to exploit and reuse or combine green energy sources in data centres to lower brown energy consumption and CO 2 emissions. This paper presents a comprehensible overview of the current data centre infrastructure and summarizes a number of currently available energy efficiency strategies and renewable energy integration into data centres and its characterization using numerical models. Moreover it would be necessary to develop dynamic models and metrics for properly understand and quantify the energy consumption and the benefits of applying the incoming energy efficiency strategies and renewable energy sources in the data centres. Thus, the researches or investors will be able to compare with reliability the different data centre designs and choose the best option depending on the renewable energy sources and capital available. [ABSTRACT FROM AUTHOR]

Abstract: The paper describes the modelling and analysis of a 10MW chilled water distribution system that is used for the cooling of parallel Data halls. During an unplanned site power failure, the Chillers may go offline for some minutes, affecting the temperature and delivery of chilled water to the Data hall cooling units. This may cause the air temperature within the Data halls to rise. The ultimate test of robustness is to ensure that the IT equipment is adequately cooled during this time. This work outlines the key findings from the thermal response of the cooling system to a site power failure. The entire chilled water network that comprised the primary and secondary plant was modelled, including components such as pumps, valves and Chillers. A transient analysis was conducted to predict the rise in water temperature at different locations in the system. Computational fluid dynamics was then adopted to predict the air temperature reaching the IT equipment, therefore confirming the capability of the design to steer clear of effects such as thermal runaway. The findings demonstrate that confidence in the omission of expensive buffer vessels and UPS backed plant could not have been achieved without the advanced transient analysis conducted here. [ABSTRACT FROM AUTHOR]