The biggest barriers to risk reduction in any system are human unawareness of risk, a lack of formal channels for knowledge transfer within the life cycle of a facility and onto other facilities, and design complexity. Significant risk reduction can only be achieved through active engagement of all facility teams and through each disparate stage of the data center's life cycle. This explains the content of the adapted Kolb cycle to show how risk in the data center can be better managed. If there is no way to transfer knowledge in the data center life cycle, the quadrants of the Kolb cycle become silos with expertise and experience remaining within them. Failure mode and effect analysis is a “bottom-up” design tool used to establish potential failure modes and the effects they have for any given system within the data center.

The GreenSCIES project aims to deliver low carbon, affordable energy through a novel smart energy system that connects flexible electricity demands such as heat pumps and electric vehicles to intermittent renewable energy sources such as solar power. This paper presents the results of the feasibility study of a 5th generation district mobility, power and heat network in the London Borough of Islington. The smart network facilitates the transition to electric vehicles and vehicle-to-grid supply to make the most of intermittent renewable energy and ensure end-users always get the best tariff. Heating and cooling are provided by heat pumps in buildings connected to a local network, which integrates thermal energy storage and waste heat recovered from local datacentres. Artificial intelligence underpins the system optimisation and demand side response. Low carbon heating and cooling is achieved by sharing heat between buildings and by shifting the timing of their demand to off-peak cheaper electricity; this requires a sophisticated control system and thermal energy storage. The feasibility study also worked with key stakeholders to understand the views of end-users and others in the supply chain. The role of key thermal energy providers such as Transport for London and Data Centres is fundamental. The preliminary results indicate that the smart network can deliver up to 25% reduction on energy bills and 80% CO2 savings compared to a baseline scenario with gas boilers, chillers and grid electricity. As the electricity grid decarbonises further it is forecasted that the network will tend to net zero carbon before 2050. The GreenSCIES concept is suitable to be replicated throughout the country and has the potential to become a world-leading example.

The development of the Green Public P rocurement (GPP) criteria for Data Centres, Server Rooms and Cloud Services is aimed at helping public authorities to ensure that data centres ’ equipment and services are procured in s uch a way that they deliver environmental improvements that contribute to European policy objectives for energy, climate change and resource efficiency, as well as reducing life cycle cos ts. Acknowledgements This report has been developed in the context of the Adminis trative Arrangement "Development of implementation measures for S CP ins truments (SUSTIM)" between DG Environment and DG Joint Research Centre. The person respons ible at DG Environment was Enrico Degiorgis. The authors would like to thank the experts involved in the development of this s tudy for the valuable input provided, includ ing the colleagues from DG GROW, DG CLIMA and other European Commiss ion DGs providing inputs and support, the members of the GPP Advisory Group and the organisations participating in the stakeholder consultation process listed in the Appendix IV at the end of this report. The authors are als o grateful to Mr. Rick Nowfer and Ms. Carmen Ramirez (DG JRC) for the s upport provided during the stakeholder consultation process and for the editorial support, and also to Ms. Anna Atkinson (DG JRC) for the proof-reading.

Life cycle assessment of data centers has indicated that the main environmental impacts stem from the embodied impacts, energy efficiency and source energy mix of the facility mechanical and electrical systems and equipment and IT equipment. Metrics to describe the in-use efficiency of the power and cooling infrastructure are well adopted, however the other areas often go unmonitored, in part due to lack of data, metrics and difficulty of measurement. Without a holistic view of impact, burden shift may occur, i.e. where action is taken to reduce the environmental impact of one area which moves or increases the impact to another area. Life cycle assessment considers a range of environmental impacts grouped into areas of protection: human health and climate change, ecosystem quality and resources. In this paper a metric comprising separate measures for each main area of impact is described, identifying key variables and analysing their range so that their effect on environmental impact may be understood and used as a basis for decision making. The operational component includes the influence of energy and water consumption, PUE, WUE and renewable energy usage. The embodied component considers variables such as utilization, equipment lifecycle, materials and disposal in mechanical and electrical systems and plant and IT equipment. These are related to the IT output via a productivity proxy. The paper includes preliminary analysis of the application of the metric

Data centres are large energy consumers, which have become more energy efficient in recent years due to increased awareness of opportunities, increasing energy costs and corporate social responsibility pressures. A lifecycle assessment approach identifies two other significant areas of impact: the embodied impact of IT equipment and mechanical and electrical plant, and the electricity source used in operational and embodied processes. Many data centre operators publicise their energy efficiency, some also report on their carbon footprint. However, there is a need for simple tools in order to help operators better understand and quantify the embodied impact and inform green procurement. Focussing purely on energy efficiency may cause a burden shift, e.g. by replacing equipment with more efficient equipment but increasing the embodied impact. The total environmental impact could remain the same/increase, but with the perception of a ‘greener’ data centre. Although currently there is limited data available for data centre life cycle assessments and the process is resource intensive, research has identified which factors significantly impact a facility’s environmental impact. This knowledge should be used in the design process and throughout the data centre lifecycle to minimise data centre environmental impact. Practical application: As the data centre industry continues to grow and its sustainability receives closer scrutiny, it is important to increase awareness of where its highest environment impacts lie and analyse the factors which influence this. This can help inform policy and decision-making to support the design and operation of data centres which are truly more sustainable. It is important that this research is not just theoretical but can translate into practical actions which can be implemented in a cost-effective manner for the benefit of everyone. The current focus in industry has been energy consumption and energy efficiency; many practices which were considered innovative a few years ago have now become standard best practice. It is time to examine which other areas should be prioritised for improvement.

Historically, the rising cost of energy has been a huge driver for data center energy efficiency, and the contribution of this consumption to climate change is ever more evident. As the industry begins to look beyond energy consumption, it has become aware that environmental impact derives not just from energy consumption, but also from our use of natural resources. To ensure optimization measures do not cause a burden shift, these interdependent issues should not be considered in isolation. Data centers consume energy to power and cool IT equipment. Current optimization efforts largely focus on the operation of cooling technologies. These can be categorized simplistically according to their use of air or water to remove the heat created by the IT equipment. Design decisions are based on the theoretical energy consumption, and resulting running costs that a certain technology has in a given location. However, water is a valuable natural resource and currently it is difficult to expand this analysis to consider its consumption alongside that of energy. It is also difficult to understand whether indirect impacts of water and energy consumption outweigh any savings of one technology over another during operation. For example, water is consumed during the production of energy, the amount of which depends on the source of generation. To understand these impacts a life cycle approach is required. Such an approach acknowledges that water and energy are consumed from the moment raw materials are extracted and combined into process materials, to the point that it is used and then disposed of. A full life cycle impact of the different cooling technologies in a data center would consider the impacts of operation as well as those embodied in them. This, however, is a time-consuming process. Instead, the industry needs life cycle based tools and metrics that can expedite this decision process. Using life cycle assessment (LCA) to determine a single numerical value for total environmental impact, the work in this paper provides simple equations that allow designers to understand the environmental implications of their water and energy use in different parts of the world. A number of theoretical case studies are then used to demonstrate its application. Future work should look to include embodied impacts.

Energy efficiency has become increasingly important in the data center industry, driven by rising energy prices, environmental legislation, corporate social responsibility pressures, and competition. Energy efficiency is part of sustainability, however, consideration of other aspects such as the embodied environmental impact of materials, components, and systems is needed for a holistic view. Life-cycle assessment (LCA)is a useful methodology that examines wider environmental impact including areas of protection such as climate change, ecosystem quality, human health, and resource depletion.The industry is starting to become more aware of these issues and is developing metrics to quantify performance. This paper describes key data center sustainability issues identified by the life-cycle assessment of data centers and proposes how the industry could approach its environmental responsibilities in order to capitalize on the business opportunity as well as demonstrating sustainable leadership.

Data centres consist of data halls, or buildings, containing rows of IT server racks, which are used to store, process and transmit information from connected computer networks. There are estimated to be more than 2 million server racks in the UK. Data centres are large energy users, being currently responsible for at least 1.5% of the electricity demand for the whole of the UK and with increased internet use this is projected to grow by up to 20% per year up to 2020. Electricity is used both to power the IT servers and for the cooling equipment, such as air conditioning systems, which are used to remove the heat generated by the IT servers. This heat is normally discharged to the ambient air; however, if the heat could be recovered and reused, it would represent a significant heat resource. This paper describes the range of approaches available for the cooling of IT servers and their potential for waste heat recovery and reuse. One waste heat recovery application that has been recently proposed, for example by the UK's Department of Energy and Climate Change (DECC), is as a heat source for district heating networks. The use of heat pumps to boost the temperature of the waste heat rejected by data centres, in order to meet the heat input requirements for heat networks is explored in this paper, and the potential energy, carbon and cost savings available are presented. The matching of potential data centre waste heat sources to the heat requirements for a number of London districts is also reported. (C) 2015 Elsevier Ltd. All rights reserved.

A novel method for the cooling of large scale heat generating processes in cities has been identified, namely the use of mains water. Applications include data centres, underground railways, supermarkets, hospitals and large buildings in general. Two applications for this cooling method which are currently being investigated are the cooling of London underground stations and the cooling of data centres, and this is the subject of this publication. Mains water is distributed across London through a network of pipes, and varies in temperature between 5 and 20°C during the year. For much of the year, there is potential to raise the water temperature by a few degrees, while maintaining the mains water temperature within its current maximum limit. In fact, to increase the temperature of the entire mains supply by 1°C requires heat input of the order of 100 MW. Consequently, mains water provides a large cooling resource, which could be used to replace mechanically cooled chilled water for many air conditioning system applications, especially for large scale industrial use. In London alone mains water could deliver continuous cooling of more than 600MW. London underground stations and data centres typically have cooling loads ranging from 0.5 to 5 MW, and a large number of them could have their cooling needs met by this method. The results of calculations for potential energy, carbon and cost savings by using mains water for cooling for these applications are presented, and possible methods for transferring the heat are discussed. A number of other systems to which this cooling method could usefully be applied have also been identified and are described.

A novel method for the cooling of large scale heat generating processes in cities has been identified, namely the use of mains water. Applications include data centres, underground railways, supermarkets, hospitals and large buildings. Two applications for this method are the cooling of London Underground (LU) stations and data centres, and these are the subject of this publication.Mains water is distributed across London through a network of pipes, and varies in temperature between 5 and 20 degrees C during the year. For much of the year, there is potential to raise the water temperature by a few degrees, while maintaining the mains water temperature within its current maximum limit. To increase the temperature of the entire mains supply of London by 1 degrees C requires heat input of the order of 100 MW. Consequently, mains water provides a large cooling resource, which could be used to replace mechanically cooled chilled water for many applications. In London alone mains water could deliver continuous cooling of more than 500MW (for at least 8 months of the year). LU stations and data centres typically have cooling loads ranging from 0.5 to 5 MW, and a large number of them could have a substantial proportion of their cooling needs met by this method. The results of calculations for potential energy, carbon and cost savings by using mains water for cooling for these applications are presented. A number of other applications to which this cooling method could be applied have also been identified.

The data centre industry grows with our increasing demand for IT services; energy forms a large part of data centre operating costs. Operators face increasing pressure to reduce their environmental impact and deliver competitively priced services to support users. However, many existing data centres were designed without a ‘green’ design brief; priorities were focussed around infrastructure redundancy. There are significant opportunities to implement modifications to design and operation and reduce operating costs, particularly to cooling systems, including managing data hall air, operating at higher temperatures, using free cooling and optimising for part load operation. Energy analysis can identify areas for improvement, often with short payback periods. This enables operators to realise massive reductions in energy (and sometimes capital) costs, whilst still delivering a reliable service. Practical application: The paper describes the challenges of reducing energy consumption and operating cost faced by those working in the data centre industry, along with tools and solutions. Details on where and how to achieve energy savings are presented, whilst maintaining the required availability for both new build and legacy facilities. Practical examples of how to put theory into practice are explained, including case studies where real clients have implemented improvements.

Data centre energy consumption has grown significantly in recent years; cooling energy forms a substantial part of this and presents a significant opportunity for efficiency improvements. With best practice air management in place, it is possible to reduce airflow and increase supply air temperatures. This can be achieved through separation of hot and cold air streams by cold aisle, hot aisle or rack exhaust containment systems. Once server air inlet temperatures are within a narrow range, close to the supply temperature from cooling units, it is possible to increase temperature set points with the confidence that IT equipment receives air at an acceptable temperature. This allows energy savings to be realised through more efficient refrigeration cycle operation and increased opportunities to benefit from free cooling; in many cases it may be possible to remove refrigeration altogether.There are several different methods for free cooling using economizer cycles in data centres, which can be used instead of / in conjunction with traditional refrigeration for full or partial free cooling. These include direct and indirect air side and water side free cooling systems. The typical overall approach (difference between ambient wet bulb condition and data hall supply air temperature) is given for each of the free cooling methods, together with the projected maximum design ambient temperatures in different locations and the resulting maximum data hall supply air temperatures.The results indicate the extent to which zero refrigeration is possible for each type of free cooling system throughout the USA, when supplying air into the data hall within the ASHRAE recommended and allowable ranges. Zero refrigeration solutions result in a significant saving on capital cost due to the reduction in mechanical plant and associated supporting electrical infrastructure i.e. switchboards, generators, power distribution etc. In many US climates 100% free cooling (zero refrigeration) is possible and significant operational and capital cost savings can be realised.

This paper presents a method to evaluate air flow effectiveness of both traditional raised floor designs and non-raised floor air-conditioning designs for data centers. Metrics are developed that will easily permit owners, engineers and operators to measure and quantify the performance of their data center air distribution systems or changes that they make to their cooling systems to improve air management and hence cooling system efficiency. The metrics incorporate and integrate together the major factors that decrease the effectiveness of computer room air cooling. These metrics, which are covered in the paper, include; negative pressure flow rate (air induced into the floor void), bypass flow rate (from floor void directly back to the air-conditioners without cooling servers), recirculation flow rate (from server outlet, back into server inlet) and the balance of CRAC and server design flow rates. Examples of the application of these metrics are also presented. Additionally, benchmarking data of bypass and recirculation collected from over 60 data centers during energy audits are presented. The benchmarking data clearly identifies potential energy saving opportunities when compared to ideal (no bypass and no recirculation). Consequently, one can use the benchmarking data to compare a given data center to others and to measure progress in reducing recirculation and bypass levels as energy conservation measures and best design practices are implemented in the data center. The methodology presented in this paper offers the advantage to establish quick understanding of the air management in the data center in fairly short amount of time using internal resources once the presented guidelines and lessons learned are followed. Performing CFD, which may be required in some cases, requires specialized engineers with sufficient knowledge in data center air flow paths, racks and server types, cooling equipment and power distribution units in order to build reliable air flow models using any of the commercially available CFD packages. The aforementioned requirements render the CFD simulation an expensive service. Hence, CFD simulation should be used when air management analysis falls short, example of such cases include planning for future IT growth using specific hardware in specific location.

This paper presents a summary of the energy audit and optimization studies conducted on more than 40 data centers. Comparison of data center energy efficiency metrics is presented. Those metrics include energy utilization metrics such as the Power Usage Effectiveness (PUE), Data Center infrastructure Efficiency (DCiE), mechanical PUE, electrical PUE and thermal or air management metrics such as bypass and recirculation airflow ratios. Additionally, percentages of cooling system, fans, UPS losses, and lighting to total data center power were analyzed and presented. The impact of climate zone as well as the operational load density compared to design load density were considered as well. These metrics incorporate and integrate together the major factors that decrease the effectiveness of computer room air cooling and the entire data center infrastructure. The energy utilization metrics determine the extent of the efficiencies of the data center supporting mechanical and electrical infrastructures. Interestingly, the database indicated that small data centers [Raised Floor Area (RFA) <10,000 ft(2)] or corporate data centers have higher average PUE than the larger ones. Small data centers were observed to have partially populated IT equipment racks and floors, oversized and aging cooling systems, higher levels of air mixing (recirculation and bypass air) in the raised floor areas, no implementation of free cooling, low UPS load factor, and no direct cooperation between the IT and the facilities departments. However; enterprise data centers were observed to implement more energy saving techniques such as "free cooling" as well as higher level of cooperation between IT and facilities. Many of those large data centers were also observed to participate in various professional IT and facilities organizations 'seminars to stay informed about new advances in their field as well as industry best practices.

This paper presents a means to quantify airflow performance of both traditional raised floor designs and non-raised floor air-conditioning designs for data centers. Metrics are developed that will readily permit owners, engineers and operators to measure and quantify the effectiveness of their data center cooling systems or changes that they make to their cooling systems to increase air cooling efficiency. The metrics incorporate and integrate together the major factors that decrease the effectiveness of computer room air cooling. These factors, which are covered in the paper, include; negative pressure flow rate (air induced into the floor void), by pass flow rate (from floor void directly back to the air-conditioners without cooling servers), recirculation flow rate (from server outlet, back into server inlet) and the balance of CRAC and server design flow rates. Examples of the application of these metrics are also presented.