This graph rich whitepaper compares the two types of economizers – fluid and air. The pros and cons of each one are explained in detail and how they can be utilized in places as diverse as Atlanta and Chicago. Considerations range from capital expenditure costs, best operating hours, duct work, estimating annual energy savings and safely bringing in outside air.

Special consideration must be given to the data center climate control system because sensitive electronics should only be subject to systems that are proven. However, with a potential of 50% energy cost savings this technology cannot be overlooked and deserves a serious review from the IT strategist.

This white paper from MovinCool examines the benefits of using ceiling-mount air conditioners to keep server rooms and closets cool inside heated buildings. It discusses the scenarios in which overheating can be missed or ignored, explains the differences between mini-splits and precision cooling systems, and the drawbacks associated with precision units. Next, the functions of a ceiling-mount air conditioning unit and the advantages to utilizing them are explored, as well as what to look for when choosing a self-contained, ceiling-mount air conditioner.

Learn the many advantages of ceiling-mount air conditioning systems and the dangers of overheating. Click here to download this white paper on the benefits of self-contained, ceiling-mount air conditioners.

This white paper from Raritan answers some of the most challenging questions associated with energy management while providing detailed explanations of how to correct some of the most common false assumptions regarding power consumption.  It goes on to discuss methods for measuring the difference between IT equipment power load vs. total facility power load, and calculating Power Usage Effectiveness (PUE).  Lastly, it demonstrates what to do with the knowledge gleaned from these calculations, and how to make the best use of it while planning your data centers energy management strategy.

Learn the importance of accurately calculating your data center’s power needs.  Click here to download this white paper from Raritan on energy requirement calculations and the advantages that come with real-time power monitoring.

By their nature, mission critical facilities such as Internet data centers are prime candidates for power monitoring systems. By employing monitoring systems to analyze system-wide historical and real-time power data, facility managers can reduce the cost of electricity and improve its quality and reliability.

Where high accuracy metering, disturbance recording, transient detection or harmonic analysis is needed, there is no substitute for power monitors. So if you’re going to deploy power monitors in a data center, this paper offers several key guidelines to keep in mind.

“The rapid rates of growth in data center electricity use that prevailed from 2000 to 2005 slowed significantly from 2005 to 2010, yielding total electricity use by data centers in 2010 of about 1.3% of all electricity use for the world, and 2% of all electricity use for the US,” Koomey writes. The report, “Growth in Data Center Power Use 2005 to 2010,” was prepared for the New York Times, which summarizes the findings. The full report is available via Koomey’s web site.

The moderating pace of data center energy use is “driven mainly by a lower server installed base than was earlier predicted rather than the efficiency improvements anticipated in the report to Congress,” writes Koomey, whose 2007 report to Congress and the Environmental Protection Agency has framed most subsequent discussions of data center energy usage.

Economic Slowdown and Virtualization Cited

Koomey says companies have been buying fewer servers than anticipated due to the economic slowdown and the benefits of virtualization, which allows users to make better use of their server capacity. The study downplays the potential impact of an industry-wide effort to develop metrics and share best practices on energy efficiency, but indicated that these efforts could begin to have a larger impact in the near future, as more computing workloads shift to cloud computing platforms hosted in cutting-edge facilities.

In compiling the data, Koomey used estimates of installed servers from the research firm IDC. He assumed a data center Power Usage Effectiveness (PUE) rating of between 1.83 and 1.92, based on estimates of the average PUE reported in recent samplings by the EPA Energy Star Program and the Uptime Institute. While some cloud computing data centers have PUEs in the 1.1 to 1.3 range, Koomey noted that less efficient in-house corporate data centers account for the largest number of servers. “That (PUE) assumption will need to be revisited as cloud computing becomes more widely used,” he wrote.

Energy Usage Slows During Building Boom

The New York Times has been investigating data center energy use since early 2010, with a particular focus on Google’s data centers. “Data centers’ unquenchable thirst for electricity has been slaked by the global recession and by a combination of new power-saving technologies,” writes The Times John Markoff. “The decline in use is surprising because data centers, buildings that house racks and racks of computers, have become so central to modern life,” “The slowdown in the rate of growth of electricity use is particularly significant because it comes in the midst of the biggest build-out of new data center capacity in the history of the industry.”

The five-year period reviewed in the  Koomey tracks a time of dynamic growth for the data center industry, in which Google, Yahoo, Microsoft, Facebook and Apple all built enormous cloud data centers, while service providers filled space at wholesale data centers built by Digital Realty Trust and DuPont Fabros Technology.



On May 17th the Data Center Efficiency Task Force issued a 14 page document entitled “Recommendations for Measuring and Reporting Version 2 – Measuring PUE for Data Centers”  – also known as PUE 2.

While PUE was originally created by The Green Grid in 2008, it was adopted in early 2010 by the Data Center Efficiency Task Force, a group consisting of 7×24 Exchange, ASHRAE, Silicon Valley Leadership Group, the U.S. Department of Energy’s Save Energy Now Program, the U.S. Environmental Protection Agency’s ENERGY STAR Program, United States Green Building Council, Uptime Institute and The Green Grid.

We’ll hear thoughts from members of the task force shortly. But first, let’s take a look at what’s new.

The updated PUE version is meant to clarify and reiterate the updated measurement requirements of the PUE metric and presumably prevent “PUE envy.” It reflects and reiterates the “Harmonizing Global Metrics for Data Center Energy Efficiency” definition of PUE which was released by the task force in February of this year.

Energy Rather Than Power

While it is still called PUE, it now specifies energy usage (expressed in KWH) not power (KW) as the primary basis for the metric. This still seems to be one of the sources of confusion to those using and quoting PUE numbers for their data centers.

There are four PUE measurement categories (0-3), of which three upper categories (1-3) specify annualized energy consumption as the basis for the calculations. Even PUE Category 0, which still allows power demand expressed in KW, now requires that the calculation be based on the highest power used by the facility, not just the lowest power measurement taken on a cold night when the chillers are off.

“PUE Category 0: This is a demand based calculation representing the peak load during a 12-month measurement period.”

This should help level the playing field of some seemingly exaggerated PUE claims.

Guidance on Measurement

The PUE 2 document is an enhancement and continues to follow the “3 Guiding Principles” and the “Harmonizing Global Metrics” document issued in February by The Green Grid and the Task Force and also adopted by some international organizations.
Moreover, PUE 2 includes more details on how to properly measure and calculate PUE for data centers located in a mixed use building, in particular building-supplied chilled water or condenser water.

One of the significant changes in PUE 2 which may be easy to overlook, is the following caveat regarding the requirement to reference the PUE category when proclaiming a data center’s efficiency.

“When publishing PUE, the category must clearly be indicated using a subscript e.g. PUE0, PUE1, PUE2, PUE3. A PUE reported without the subscript is not considered to be in compliance with these recommendations.”

It would seem that very few (if any) of those who have previously made public proclamations of their PUE results have indicated which PUE category methodology and protocols they used to derive their claimed results. Going forward they will hopefully include the category in future PUE announcements. It should be interesting to see how many organizations will adhere to this requirement in any new crop of PUE announcements.

But few enterprise data centers are following suit, according to Zahl Limbuwala, chairman of the Data Center Specialist Group at BCS, the leading IT industry group in the UK.

“We’re still stuck at low temperature points,” said Zimbuwala, who gave a presentation at the Google European Data Center Efficiency Summit Tuesday in Zurich, Switzerland. “All the work the industry has done on this issue still needs to roll through. It really hasn’t had the impact we thought it might.”

Data Centers Weigh Risk vs. Reward

Most data centers operate in a temperature range between 68 and 72 degrees F (20 to 22 degrees C), and some are as cold as 55 degrees F (!2 degrees C). But Google and others have increased the data center temperature to 80 degrees F (about 27 degrees C).

Raising the baseline temperature inside the data center – known as a set point - can save money spent on air conditioning. By some estimates, data center managers can save 4 percent in energy costs for every degree of upward change in the set point. But nudging the thermostat higher may also leave less time to recover from a cooling failure, and is only appropriate for companies with a strong understanding of the cooling conditions in their facility.

The leading U.S. industry group for heating and cooling professionals, ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) increased its recommended operating range for data centers from 77 degrees to 81 degrees in a 2008 update.

Limbuwala reviewed data from a survey of BCS data center operators, which found that the majority of data centers continue to operate at 22 degrees C (72 degrees), with most of the remainder between 20 and 24 degrees C.

ASHRAE has just released new, expanded guidelines for server rooms based on the type of equipment and application, and the level of control the operator has over the environment. For data centers running mission-critical operations, ASHRAE has maintained the 2008 upper range of 80.6 degrees. It has also created several new categories for operators of data centers who have strong control over the environment and manage  reliability using groups of networked data centers, such as Google or Microsoft or Yahoo. The upper range for those facilities can now range as high as 113 degrees F (45 degrees C).

Impact on Legacy Facilities and Equipment

The new guidelines draw clear distinctions between different types of facilities, according to Don Beaty, founder of DLB Associates and active member of ASHRAE Technical Committee 9.9. Beaty said many data centers covered by the ASHRAE guidelines are either older facilities or running legacy equipment that may not tolerate warmer environments as well as new equipment.

Harkeeret Singh of Thomson Reuters, who gave a presentation in Zurich on behalf of The Green Grid, emphasized the need for data center operators to be closely monitoring and managing conditions within their server rooms.

“Widening the temperature is more relevant for new data centers,” said Singh. “We can’t raise the temperature in the data center without dealing with airflow management. First do all the airflow management tasks, then raise the temperature.”

So what is the forward thinking, budget conscious, professional to do? Simple, make the proper one time investment into a proven analytics program. Software is now available at a fraction of consulting costs. CFD (computational fluid dynamics) analysis can forecast thermal problems from room level down to the individual PC board.

When viewed from the rack, row, room, or building level (or even across a network of data centers at the enterprise level), ARC provides a simple way to answer the question.

Typically, most data centers don’t calculate ARC explicitly. Instead, operators set a simple alarm threshold on the Actual Load of each device. For example, if the power load reaches 50% on a device (or more often 40% when de-rating), then the device or the monitoring system will throw an alarm.

However, this simple approach to thresholding based on device power usage doesn’t effectively capture all the conditions of the broader power distribution system. There can be hidden capacity that allows for safe failover, even though simple device-level thresholding suggests otherwise.

Where Can I Add Load?

The goal of system ARC is to identify where you can handle additional load without sacrificing system redundancy. To calculate ARC for power of a device in a dual-feed situation, the calculation is simply:

ARC = {Device Capacity}/2 – {Actual Load}

In most cases, the Device Capacity will be de-rated to allow for some margin. In the case of power capacity, it is common to de-rate apparent power (kVA) capacity by 80%. ARC can also be expressed in real power (kW) if you know or can estimate the power factor of the load. It is even more important to de-rate the capacity in the case kW measurements to allow for potential load problems that could degrade power factor.

For operational alarming, calculate ARC continuously and alarm if it goes negative for any subsystem. For reporting, and determining where to install new equipment, be sure to use the minimum ARC measured over time, or equivalently, calculate ARC above with “Actual Load” replaced by “Maximum Actual Load.”

Below is an ARC-based dashboard in action:

An ARC-based dashboard. Click for large version.

Here, the top panel shows ARC calculated for 6 different data centers, along with a measure of cooling overhead in the same units, where available. The lower panel shows the drill down for one of the sites.

When calculating the overall ARC for devices in parallel, you can add the ARCs of the individual units. For instance:

UPS A has 10 kVA ARC
UPS B has 8 kVA ARC

Together, they have 18 kVA ARC. If we have another UPS pair supplying a different load, their ARC can be added to this set in order to get the system ARC. The rule of summing ARC for parallel systems doesn’t depend on the systems be redundant.

Calculating system ARC from the individual device ARCs in this way assumes that the capacities of both parallel components are the same. This is most often the case, but in the rare instance that it is not, then you have to total the actual load across the devices, and compare it to the (de-rated) capacity of the smaller device. This ensures that the most-limited device can handle the entire load.
Interestingly, it is possible to have a safely redundant system even though one of the individual devices has a negative ARC.

For example:

UPS A has 3 kVA ARC
UPS B has −2 kVA ARC

The net ARC of the system is a small but safely positive 1 kVA. In this case, even though one UPS is nominally overloaded according to the simple one-device threshold, either UPS can fail without dropping any load. Note that a simple single-device alarm threshold would show UPS B in alarm, and trigger a potentially costly load rebalancing.

Exact Redundancy Configuration Needed

In order to evaluate a negative component ARC, one does need to know the exact redundancy configuration. Thus, it is important to evaluate ARC for each subsystem and then roll it up to the data center as a whole.

When looking at the entire power chain, as with any capacity measurement, the system is limited by the weakest link in the chain. The component, or more accurately the collection of parallel components, with the smallest ARC will be the limit of the entire system. In the scenario above, if the PDUs downstream of the UPS have a collective ARC of 20 kVA, the load will still be limited to the 1kVA of the UPS.

Some questions may arise when the load is imbalanced, as in the UPS examples above. Such imbalances may arise because some of the load is not configured redundantly. We hope instead that some loads are switched, and simply not balancing themselves between the two power paths. The ARC calculation doesn’t depend on knowing such details. Of course, any non-redundant load will be dropped if it loses its power source; however, as long as the system ARC is positive you know that any redundant load will be protected regardless of which power source is lost.

In summary, the goal of system ARC is to identify where you can handle additional load without sacrificing system redundancy. With parallel equipment, you can total the ARC of all components if they have the same capacity rating. When looking at ARC along the power chain, the correct system value will be the minimum ARC of any one set of components.