In this months CISBE Journal, our head of innovation, Richard Clifford, argues that early collaboration is essential to ensure customers understand and avoid the hidden costs of energy saving measures within data centres.
Data centres are inherently energy intensive, making up as much as half of a company’s energy consumption in some cases. Naturally, as financial, regulatory and CSR pressures have increased, energy efficiency has been pushed to the top of the agenda for data centre design. A myriad of options available in the market, exacerbated by different consultants all championing their own approach or solutions, has led to confusion and in some cases an inherent lack of understanding for the end user. In the race to specify efficient data centre estates, options and outcomes are not being fully explored, which can lead to increased costs and compromise overall CO2 reductions in the long term.
Part of the problem is that the industry’s go to metrics can be misleading or easily manipulated to appear more attractive. Specifiers often focus on metrics because at a base level they provide an easy reference point that can be used to evaluate the efficiency of different options. Yet, measures that bring the best results on paper may not offer the most efficient or cost-effective option and can, in extreme cases, lead to long term operational faults.
Most of these measures also work on an assumption that the facility is operating with a full IT load, which rarely happens in most cases. Energy efficiency naturally decreases at lower IT loads and suggested levels can take longer to come into play, if ever. Solely investing in a design that offers a good efficiency metric can leave a business open to higher operational costs than expected later down the line.
For example, PUE (power usage effectiveness) – a ratio of how efficiently energy is used by a data centre’s computing equipment in contrast to cooling and other overheads – can be improved by raising rack temperatures, which has very little effect on savings, as any energy saved by turning down cooling systems is shifted to server fans.
Metrics like PUE don’t paint a full picture on efficiency and, as consultants, we should be working with all our stakeholders to ensure they understand the true implications of how different solutions and routes will affect their facilities in the long term.
Many of the energy efficiency measures available are key examples of this and their long-term implications need to be thoroughly understood before they are committed to. Without proper consideration, some can create hidden costs elsewhere and cancel out any potential saving, or, in the worst-case scenario, have a negative impact on the facility’s resilience, increasing the risk of downtime.
Fresh air cooling, often considered one of the most eco-friendly cooling methods, is a textbook example. On paper it has almost no carbon footprint and can be particularly cost-effective for facilities located in colder climates. Such alluring benefits are causing many customers to specify these systems without considering suitability or being aware that operating these systems long-term can be more complicated than first anticipated. Fresh air cooling is highly dependent on location – it is easily contaminated by pollution or seawater which can damage hardware and bring high replacement costs. Preventing this damage means investing in additional cleaning and maintenance which brings more overheads and ultimately, a larger CO2 footprint if replacement parts are needed. Likewise, fresh air needs more complex control systems such as fire detection and suppression which all add further capital and operational costs.
Another cooling example impacting efficiency are the new changes to F-Gas legislation, which have brought forward price rises related to the management of stalwart gases such as R404A and R410A. This could have a large impact on pumped refrigerant DX systems, and lead to significant maintenance issues despite their lower capital costs.
Collaboration is key
It may be an attractive option to choose methods that appear to represent a lower upfront investment but without full consideration of the operational lifecycle, any financial or carbon savings may be eliminated in the long term. Many end-clients are stung because they don’t take a wide enough view of their data centre’s management, agreeing to efficiency measures without consulting the teams responsible for the day-to-day running of the facility.
Early consultancy and collaboration at the design stages is vital to prevent this from occurring. We should be ensuring that all stakeholders, including FM and operational teams, are involved in the design process to ensure the operation and maintenance of the facility is considered from the outset. This allows any potential pitfalls to be flagged before any decision are set in stone. It also means all teams can work together to argue for models that may cost more initially, but offer greater long-term efficiency and business flexibility.
Efficiency will always be a concern for the industry, as it should be. But this needs to go beyond just meeting metrics. By considering a facility’s lifecycle rather than just initial costs, environments can be created that save money and energy throughout the course of their use. As consultants we need to be driving this shift in focus to ensure data centres are built with long-term operation in mind.
This article was first published in the April edition of the CIBSE Magazine
(This is our final blog in our PUE series)
When measuring efficiency in the data centre PUE gives us a starting point but, as with most standards, does not necessarily meet all the needs of the industry. Although we’ve touched on some of the limitations of PUE in our previous blog, it’s important that data centre specifiers and managers are aware of the challenges of using the PUE metric as an indicator of overall efficiency and are not mislead by some PUE claims.
Calculating the PUE metric takes time and effort and although the guidelines are very specific, it can be challenging. As we close off our series on PUE here’s our top five list of points to note when looking at PUE figures:
The time of day, the points at which the monitoring takes place, and the frequency that data is collected all influence the PUE results and make it very difficult to have an accurate comparable PUE indicator. There will be spikes in loads at different times in the day and even different times in the year. A simple example is that on the hottest day of the year more cooling is going to be needed than on the coldest day of the year. (See the full list of requirements on our first blog – What is PUE and Why is it Useful?)
While yearly results can help at an overview level, the ideal is to have continual daily monitoring to get a genuine impression of efficiency in a data centre. This can be quite an undertaking for a data centre manager and is more suitable to some environments than others.
Different data centre settings need different metrics. PUE is based on the premise that the data centre facility is only used as a data centre and does not factor in that other departments might also share space in the facility. It does not work well with the business model of data centre services or colocation providers either when they are not operating at maximum design capacity.
This has resulted in the Partial PUE metric that allows the active data centre zone to be measured instead of areas not being actively used for data centre services. This means that the partial PUE will indicate how efficient a data centre is at part or low load which is imperative to data centre services companies, (see our blog When is PUE not PUE).
Some managers find it difficult to understand the PUE metric and may report a PUE value of less than 1.0. This is impossible to achieve because all energy will have an output of at least 1.0 and therefore anything lower is not achievable.
Not all reporting is accurate because some of the aspects of the data centre have been excluded for example, calculations have been based only on the cooling system. Or in the case of modular designs only the electricity supply within the modular environment has been measured rather than including the electricity points actually supplying the electricity to the modular unit.
Although PUE can provide an overview of how a data centre is performing over time, the complexity of the calculations and different data centre environments means that comparing the PUE across data centres is not very meaningful. To make useful comparisons, we need to look at the PUE calculations and reporting in detail.
Efficient sourcing of energy is not included in the metric so energy-saving generation measures such as cogeneration, waste-heat re-use and local power generation are not reflected in the PUE value.
In conclusion, while PUE is a useful indicator, it is not a case of one-size fits all and analysis needs to be tailored so that it is relevant to the individual data centre environment. Correct monitoring and management, that are able to drive actionable insight are required to deliver real efficiency cost savings. You can find out more about our monitoring solutions here
When Data Centre designers and builders talk about the efficiency of the facilities they have designed and/or built in terms of the industry standard PUE, they often reference the design PUE. We look at why this can be misleading and why it is important to understand the difference.
This blog is part of a series looking at PUE and data centre monitoring; you can read our first post, which looks at what PUE is and why it is important here.
When a new facility is designed, a PUE can be calculated based on the energy consumption of the proposed plant, cooling etc. as a measure of how efficient the solution could be. So why is this a problem?
Well, the PUE figure being quoted is often based on the premise that the data centre is actually running at 100% IT load. This is often unrealistic, as most data centres, especially in the colocation market build up their loads over time, with it taking anything from three years or more to get near to operating at full-load. In reality traditional data centre efficiency rapidly deteriorates at lower IT loads (most facilities never operate at 100%). This means that the suggested power efficiency levels will not come in to play for a significant time, if ever, and operating costs will be substantially higher than indicated by the Design PUE.
Whilst Keysource is reasonably unique in the fact that we have in-house design, project management and operation teams (which allow us to constantly feedback and learn from past projects) we would expect most data centre design and build companies to understand the fact that most facilities need to be efficient not only at full load but also at part load. They should take time with you to fully understand not only the technical requirements of the facility but also your business, so they can explain and work through this with you.
When this is not done it can cause problems as, understandably, it can have big impacts on your operating costs. This limitation of the PUE calculation is of particular importance to companies that are working to tight margins to provide for example, cloud services and colocation services.
To keep operational costs under control, it is often best to consult with specialist data centre designers. They will be able to advise you on the best technologies to deploy that drive down part load operating costs from the start and who will be able to work with you to fully meet your business and technical requirements.
We recently completed a data centre for colocation specialist; ITPS (read the case study). Part of our process was to really understand their business objectives and use our experience within the regional colocation market to propose a solution that would deliver not only the highest efficiency but also allow high densities to be deployed anywhere within the data centre. Knowing that this efficiency was needed from day one the design was built to be highly efficient at part load. To further enhance this a modular solution was used to allow ITPS to deploy more cooling and plant as required rather than having it all in place on day one.
If you would like to understand more about PUE you can read our previous posts which explain the different ways PUE can be measured or download the top 10 things you need to know about PUE. As you may have guessed, it’s one of the areas we are passionate about so please call us and speak to one of the team.
We are happy to talk you through any of the issues and answer any questions about your current or planned facility’s PUE and, if required, give you some more information on how you can increase the efficiency of your facility.
Keysource, the data centre and design build specialist, has announced that it has completed the prestigious data centre for Jaguar Land Rover’s new Engine Manufacturing Centre in Wolverhampton.
Due to the use of best in class modular design and Keysource’s expertise, the 1100 square feet data centre, which was commissioned in January 2015, has been successfully completed on time and within budget.
Andy Hayes, Director, Keysource explained,
Using a modular design means that the bulk of production and preparation can be done off site which reduces costs and saves time. Typically a project of this nature would take at least 12 months to complete but using modular designs reduced this by two thirds. Along with our cooling efficiency design measures, we see this modular approach as a template for future data centres.
As planned the core datacentre module houses 30 racks with a capacity of 320Kw. It provides critical power through an N+1 UPS system and 2N standby diesel generators. The power module designed and built off-site also offers scalability to support future expansion.
Cooling efficiency has been a key specification for this project and variable speed controlled fans have been positioned so that hot and cold air are separated via the wall rather than under the floor and this has resulted in the desired achievement of PUEL2YC of better than 1.2*
For a few years now the data centre industry has been moving towards a standard measure of effectiveness for the use of power within data centres. Power Usage Effectiveness (PUE), whilst not yet a globally agreed measure is fast becoming the standard and formalising the calculation is well underway. But what is it and why should you bother?
PUE allows organisations and enterprises to gather data, measure and report the effectiveness of their data centre, or indeed data room, in terms of power use.
In simple terms, PUE is,
Total Energy Used in the Facility
Energy Used by the IT Equipment
For smaller organisations or facilities that are located within a larger mixed-use space, Partial PUE (pPUE) can be used. This allows the data centre manager to measure PUE within a set boundary such as a room or building, or an area such as the equipment owned by certain customers or departments. For example, you may want to measure the pPUE of individual data halls, rather than the facility as a whole.
The difficulty for many businesses is the availability of the data and information required. Whilst assumptions can be made and data captured at different points it does mean that comparing PUE or pPUE across market sectors is difficult. However the real value of PUE isn’t the creation of a global league table and winners awards, but more importantly PUE gives anyone with one or more data centres or data rooms the ability to measure and compare the effective use of power over time and across the business. (There are a wide range of intelligent monitoring solutions available for data centres, you can see some of the ones we offer by clicking on the link and keep an eye out for our upcoming blog post on the “5 things you need to know about DCIM”)
PUE gives everyone the ability to measure and improve the use of power in their data centres.
So what should be included in each group for the calculation?
Total Energy Used by the Facility
Plus the IT equipment listed below
Energy Used by the IT Equipment
Whilst the Total Energy Used by the Facility can often be gathered at source from the utility meter supplying the facility, or a meter just prior to the data room (for pPUE), the data collected regarding the Energy Used by the IT Equipment will be more accurate the closer the source of the information is to the individual units that consume the power. For example, gathering power usage from the installed UPS units is not as accurate as the information available from the subsequent Power Distribution Units (PDUs), which in turn is not as accurate as the data gathered from individual meters immediately prior to the IT Equipment.
PUE and pPUE account for this within the standard definition by allowing 3 variations, PUE1, 2 and 3, with PUE3 being the most accurate. There is also three different reporting frequencies; Yearly (Y), Monthly (M) or Weekly (W) with each denoting what period the data has been averaged over. On top of this you then have the data collection frequency; Monthly, Weekly, Daily or Continuously. So a PUEL3YC (which is the standard measurement we use at Keysource) would be a measurement from PDU level on a continuous basis.
Given the lack of consistency in measurements and environments it is not valid to quote a ‘world class PUE’, however it is generally accepted that a PUE of 2 or less is considered good and less than 1.4 is considered very good. A PUE of 1 means that 100% of the energy is used by the IT Equipment and therefore the physical data centre is 100% efficient, a PUE of 2 or less would mean that 50% or more of the power used by the data centre is used by the IT Equipment and so on.
There are so many factors that effect the efficiency of data centres that “snap shot” PUE figures can be misleading. For example:
Because of this, continuous reporting and monitoring is the recommended way of tracking PUE, by not only Keysource but also The Green Grid; who developed the metric in the first place.
As touched upon it is also important to take into account the different environmental conditions of different regions. As such, PUE levels cannot be compared across regions because a higher PUE in one region might be relatively better than a PUE in another region but we will look at this in more detail in another post.
Remember, the key is consistency, define your measure, data sources and frequencies and stick with them.
When a customer wanting a new facility designed and/or built approaches Keysource, they often have an idea of the PUE they want to achieve and a design is developed to meet this business need whilst also meeting the technical requirements. However as this is a theoretical figure (admittedly based on some very complex mathematics!), how can you, as the customer, be sure that this is what you will be able to achieve and what if anything should you be aware of? Find out more in our next blog looking at PUE.