datacenterefficiency metricsandmethods -...

Data Center EfficiencyMetrics and Methods

q ELEMENTS OF DATA CENTEREFFICIENCY

q SERVER EFFICIENCY

q DATA CENTERCOOLING EFFICIENCY

q UPS AND POWERDISTRIBUTION EFFICIENCY

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ELEMENTS OFDATA CENTER EFFICIENCY

SERVER EFFICIENCY

DATA CENTERCOOLING EFFICIENCY

UPS AND POWERDISTRIBUTION EFFICIENCY

2 DATA CENTER EFF IC IENCY METR ICS AND METHODS

Elements of Data Center Efficiency

in effect, what a data center is and does can define what metric is used to de-

cide what is efficient or inefficient.

So how do we judge data center “efficiency?” Because the output of data cen-

ters is not a physical object per se, we have been forced to split our metrics into

two distinct groups: computing efficiency and physical infrastructure effi-

ciency. Ultimately, the ideal metric would include both.

Computing efficiency has had a long history of metrics, almost since the first

vacuum tube mainframe could add the proverbial 01+01. In addition, the speed

of the sub-system hardware—such as memory, I/O and storage—has many of

its own individual metrics, all of which are necessary to provide the actual sys-

tem throughput.

Computing systems as a whole have many different system and industry

benchmarks. In addition, the nature of “output” is constantly changing and

being redefined.

In essence, the “system” is not just hardware that can be quantitatively meas-

ured but also the software aswell as the different tasks that it performs. That can

make it difficult to define and compare the useful work that a system produces.

In October 2007, The Green Grid, a global consortium of IT companies and

professionals seeking to improve energy efficiency in data centers, tried to ad-

dress this question and introduced the following metric:

Data Center Productivity = UsefulWork/Total Facility Power

This was part of its original PUE and DCiEmetrics. Still, this is an open

issue because the concept of what a data center’s “useful work” is makes it a dif-

ficult—if not impossible—metric to calculate or to get any groups to agree on.

This concept was also put forth in 2008 as Corporate Average Data Efficiency

(CADE) by theUptime Institute, a data center research, education and consulting

ELEMENTS OFDATA CENTER

EFFICIENCY

http://uptimeinstitute.org/content/view/273/250/

http://doe.thegreengrid.org/files/temp/574174B8-B611-1C17-0C39433C507D47D3/White Paper 6 - Efficiency Metrics PUE and DCiE.pdf

organization in NewYork, andmanagement consulting firmMcKinsey & Co.:

CADE = Facility Efficiency x IT Asset Efficiency

Facility Efficiency = Facility Energy Efficiency Percentage x Facility

Utilization Percentage

IT Asset Efficiency = IT Utilization Percentage x IT Energy

Efficiency Percentage

But neither CADE nor Data Center Productivity caught on the way the PUE

standard has taken hold. That may be because the PUEmetric is easier to im-

plement, and it does not involve any of the complexity of a common agreement

on what “useful work,” “computing efficiency” or “IT asset efficiency” is—only

direct infrastructure power measurements.

“Infrastructure efficiency” is a relatively new area of interest. Until just re-

cently, the concept of energy efficiency in data centers was a distant second to

reliability and availability.

The Green Grid and the PUEmetric came into existence only three years ago.

And although there are many critics of the PUEmetric, it has helped the indus-

try begin to address energy usage and efficiency. Fortunately, infrastructure en-

ergy efficiency is a relatively concrete area, whose components can be

quantified and calculated:

PUE = Total Facility Power/IT Equipment Power

And its reciprocal, DCIE, is defined as:

IT Equipment Power/Total Facility Power x 100%

For example:

PUE = (Total Facility Power) 200 KW/100 KW (IT Equipment Power) = 2.0

DCiE = (IT Equipment Power) 100 KW/200 KW (Total Facility Power) = 50%



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PUE and DCiE are really the samemetric, but PUE has become the more

common reference. The major positive factor of this metric is its inherent sim-

plicity, which allows it to be easily understood and, therefore, broadly accepted.

One the problems with the PUEmetric, though, is that it uses “power,” which

is an instantaneous value so that claims of a favorable PUE can be made, but

they may not represent a monthly or true annualized average of the data cen-

ter’s efficiency.

Of course, once everyone became familiar with PUE, many sites and even

some equipment manufacturers started posting how low their PUE is—

although equipment cannot have a PUE. Somemanufacturers have even

claimed that they are very close to the perfect PUE of 1.0, which would repre-

sent an infrastructure that uses no energy.

In reality, most sites have PUE ranges from 1.5 to 2.5, if they properly take

measurements according to The Green Grid’s guidelines. As a result, there are

now also references to an annualized PUE to more accurately reflect the overall

efficiency.

The ability to accurately monitor the total power to a data center facility in

real time—as opposed to waiting for the monthly utility bill—requires that sen-

sors be installed at the key measurement points. But to measure the energy

usage, the electrical distribution panels will need to have a potential voltage

transformer, as well as current transformers installed on each output circuit

leading to a cooling component.

If the entire panel is dedicated to cooling only, then you only need to monitor

the main feed to obtain the total cooling energy reading. This is lower in cost

and will allow you to calculate your PUE but does not provide detailed infor-

mation to optimize individual areas or sub-systems.

Although each type of cooling system is different, it is important to remem-

ber to include all the components—not just the computer room air conditioning

units (CRACs), such as chillers, external fan decks or pumps. Also make sure

that the system you are considering is capable of measuring actual power—KW

not just KVA—and can also record and display energy use over time and pro-



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vide useful information analysis. It should also be able to do subsets of the in-

formation, such as cooling and IT load. And last, but not least, it should be able

to calculate PUE.

In fact, during the U.S. Environmental Protection Agency’s sample study in

as part of the Energy Star for Data Centers program, it became apparent that of

the 120 sites that were involved, a majority were not capable of accurately moni-

toring the total facility load and the IT load. This was especially true for data

centers that were part of a mixed-use building.

In the end, the EPA decided to “soften” the measurement requirements and

accept the UPS output instead of the actual IT load. Ideally, the measurement

points should be more granular to allow for a more detailed analysis of where

the power is going, such as down to the rack level or even the device level. This

program has beenmore than two years in the making and originally involved

monitoring more than 120 data centers, but only 61 became valid reference sites.

Nonetheless, after 11 months of efficiency sampling, the PUE ranged from a best

case of 1.36, a worst case of 3.6 and amedian of 1.9.

In addition to the EPA program, the U.S. Department of Energy has its



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Power vs. EnergyALTHOUGH MOST PEOPLE use the terms power and energy interchangeably,they are not the same. Power is an instantaneous measurement—expressedin watts or kilowatts (KW)—while energy is power over time—expressed inkilowatt hours (KWH).The U.S. Environmental Protection Agency originally started to use the

term energy usage efficiency (EUE), during the early part of the program andlater decided to change it to power usage effectiveness, or PUE, because theindustry had adopted PUE. However, although the EPA is calling it “PUE” inits final version of the program, it has intermixed terms and has redefined itsversion of “PUE = Total Energy/IT Energy.”

http://www.energystar.gov/index.cfm?c=prod_development.server_efficiency

DC Pro Software Tool Suite, which includes a Profiling Tool and System

Assessment Tools to perform energy assessments on data center systems.

The EPA released the final official version of the first Energy Star for Data

Centers program on June 7. Although this is still a voluntary standard, the data

center industry should take heed and consider the inherent advantages of im-

proving energy efficiency now, even if only lowering operating costs.

Many vendors—both start-ups as well as major vendors—are offering energy

monitoring andmanagement packages. They can accept information that may

already be available from different brands of equipment such as the UPS, and

some can also integrate with existing building management systems.

There are a variety of systems that offer a choice or combination of hard-

wired, networked or even wireless remote units for measuring temperature,

humidity and power. The cost of the systems vary widely, based on the number

of points and type of measurement, as well as the sophistication and features of

the monitoring software package. Costs range from $5,000 to $10,000 for a basic

system to between $50,000 and $100,000 or higher for a large-scale installation.

Some vendors even offer hosted monitoring solutions for a monthly fee to lower

the capital cost of entry.

Although youmay not have given any serious thought as to how data center

efficiency may affect your existing data center’s operation, it will force you to

reconsider your existing operating practices. Additionally, it certainly will have

an impact any future data center designs and the equipment that you purchase.

Remember that efficiency has its own economic reward—an improved bottom

line.

Keep in mind that a data center is a 24/7 operation, and IT loads operate year

around. This equals 8,760 hours in a year. At 11.5 cents per KWH, each KW

saved—or wasted—represents a $1,000 a year. If your data center operates at a

PUE of 2.0, then each KW of IT load will result in a $2,000 annual cost.

Ideally, the most “efficient” data center will be one whose hardware and soft-

ware delivers the most “useful work” and is built with an infrastructure that

will support the IT load with the lowest overhead. �



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http://www.energystar.gov/index.cfm?c=evaluate_performance.bus_portfoliomanager

http://www.energystar.gov/index.cfm?c=evaluate_performance.bus_portfoliomanager

http://www1.eere.energy.gov/industry/datacenters/software.html

Server Efficiency

today’s swirling market of green technologies has brought energy-saving

technologies to the forefront of most any IT discussion. Although that’s good

news for savvy, energy-smart resellers, there is a dark side that presents a real

challenge to resellers and their customers—how to quantify energy use and re-

port it in an actionable fashion.

Some would be quick to say it is an easy problem to solve—just measure the

power used by a server in kilowatt hours, apply an hourly rate and get an an-

swer. Seems simple enough?

But there is muchmore to judging energy efficiencies than counting watt

hours. Often forgotten are essential elements, such as CPU utilization, cooling

costs, component costs and the effect of loads on the server’s subsystems.

Add to that often overlooked factors such as power supply efficiencies and

rack-based component demands, and it becomes easy to see that there is a lot

more to power efficiency than the electric company’s energy delivery fees.

JUSTIFYING A SERVER REFRESH

Server efficiency has a dramatic impact on the PUE ratio, helping to justify the

expenses associated with a server refresh, by demonstrating the impact on PUE.

Proving server efficiency is dictated by loads. For example, a server that uses

little power yet has no CPU utilization is far from efficient.

To truly estimate server efficiency, one has to look at CPU utilization as a

starting point. Many studies have shown that typical server CPU utilization

proves to be less than 15% and, in most cases, as low as single digits. Those

numbers can be vastly improved by turning to virtualization technologies,

where CPU utilization is often increased to beyond 60%, thus increasing the

inherent efficiency without requiring a server refresh.

Although increased CPU utilization does lead to increased server efficiency,



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other methodologies should not be discounted, and other measurements

should be taken before finalizing on virtualization as the only way to affordably

enhance efficiency and improve PUE.

Processing power per rack and the power footprint of each rack should be in-

corporated into efficiency calculations. It all comes down to a matter of density

—where density is defined as the number of processor cores per rack. Here, the

implementation of blade server technologies leveraging multiple-core CPUs can

increase rack density to as many as 1,024 CPU cores per rack.

That high density level has the potential to replace dozens of racks in a data

center and reduce the power and cooling footprints of the facility. Server design

is the primary catalyst for achieving densities of that magnitude.

Achieving maximum efficiencies using heavily populated racks usually re-

quires looking at the rack and the integrated components as a whole because

high CPU densities dictate that the rack be designed to deliver the power, cool-

ing andmanagement needs of the installed blades. That said, physical server

consolidation combined with virtualization technologies lead to the most effi-

cient solution.

Nevertheless, there are still many other factors that lead to quantifying server

efficiency and consist of the technologies designed to reduce power consump-

tion as well as cooling needs. A closer look at each of those technologies helps

to quantify the impact a server refresh may have on server efficiencies. Those

technologies include:

D Energy Star Specifications: Servers that meet Energy Star requirements incor-

porate various technologies to reduce power consumption and usually have a

savings percentage stated.

DNew CPUs:Many of the latest-generation CPUs incorporate technologies de-

signed specifically for power consumption reduction—such as multiple cores,

throttling, voltage drop, integrated virtualization support, ability to shut down

unused cores and across core load balancing.



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D Power Supplies:New standards are increasing the efficiencies of power sup-

plies from lows of 60% to more than 90% in the latest designs.

D Fanless Designs: The elimination of cooling fans reduces power consumption.

Fanless server designs use less energy and generate less heat.

D Increased Density:More CPUs andmore cores are being integrated into indi-

vidual servers or server blades, delivering muchmore processing power with-

out increased power consumption.

To properly calculate the potential savings of a server refresh, each of those

above elements must be considered, with the goal of reducing operational costs,

which is what improved efficiencies should lead to.

REDUCING OPERATING COSTS

A 2007 study performed by Lawrence Berkeley National Laboratory showed

that servers in a data center account for about 55% of the electricity costs. The

remaining power is used by the supporting equipment.With that in mind, it is

easy to see how servers affect power consumption and drive the power require-

ments of the supporting equipment. Simply put, server consolidation can de-

liver the largest payback over the shortest amount of time for most data centers.

Consolidating can save about $560 per year per server. Using virtualization

and newer blades, achieving server consolidations of 10 servers into one, can

deliver substantial savings for even a small company and deliver a large oppor-

tunity for a solution provider in both hardware sales and services.

Consolidation also cuts down on the amount of heat generated in data cen-

ters. But, like power consumption, it isn't just the servers that generate heat, it's

also the equipment supporting the servers that add to the heat generation. �



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Data Center Cooling Efficiency

cooling is the second largest use of energy outside of the IT load itself. In

fact, if your data center has a PUE of 2.2 or greater—andmany do—it is highly

likely that your cooling systemmay be using more power than the IT load. Con-

sequently, cooling is the area that can offer the greatest opportunity for im-

provement.

Until you have installed some form of energy monitoring andmetering, how-

ever, it is impossible to determine if you have made any improvements. At a

minimum, you will need to measure the energy to all the components of the

cooling system. This is not as easy as it sounds because many installations do

not have a centralized panel where all the cooling system components appear in

one place so that you canmeasure the total.

One of the most frequent cooling problems is an indirect byproduct of the

latest trend in “computing efficiency” improvements—virtualization and blade

servers. The average blade server requires 4 KW to 5 KW of power—some units

as much as 8 KW—and that produces much heat.

Given today’s cooling systems capacities andmethodologies, consider the

various power/heat density levels:

Heat Load per Rack

Low Density (Standard) .........................1KW to 3 KW

Moderate Density.......................................3 KW to 5 KW (one blade server)

High Density (Threshold) .....................6 KW to 8 KW (two blade servers)

High Density (Moderate)......................9 KW to 14 KW (three blade servers)

High Density (Very) ..................................15 KW to 20 KW (four blade servers)

High Density (Extreme) .........................20 KW and up

1 1 DATA CENTER EFF IC IENCY METR ICS AND METHODS


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DATA CENTERCOOLING

EFFICIENCY

This has led to the development of many different methods for dealing with

these high-density cooling loads. One of the growing trends is the increased use

of high-density localized cooling. It comes in various forms such as in-row or

overhead cooling and other forms of contained cooling, either at the aisle level

or even the rack level.

Generally this is considered “close-

coupled cooling.” Some systems use

water to remove the heat from in-row

cooling units, while others use a refrig-

erant gas. Still others use CO2 under

pressure, using phase change to handle

extreme density racks, claimed to han-

dle up to 50 KWper rack.

Besides being able to effectively han-

dle these high-density loads, close-coupled cooling is also more efficient be-

cause it requires much lower fan power to move the air 3 to 10 feet rather than

the 15 to 30 feet for traditional raised-floor cooling.

Many users are not comfortable with the concept of water being near com-

puter equipment, but early mainframes used water that ran directly into the

equipment cabinets. Coming full circle, IBM introduced the Hydrocluster in

2008, which runs the water directly into the server chassis and even into the

CPU itself.

Although not a necessarily a mainstream solution, water or other fluids are

far more efficient than air to remove heat. In addition, water allows higher den-

sities and less cooling energy. IBM has said it envisions that the heated water

could be used to heat adjunct buildings or provide hot water for facilities.

MORE CONVENTIONAL SOLUTIONS

For those who want to improve their data center’s cooling efficiency without

going to these extremes, there are manymore conventional solutions. One of



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DATA CENTERCOOLING

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Although not a neces-sarily a mainstreamsolution, water orother fluids are farmore efficient thanair to remove heat.

the most common problems is the mixing of hot and cold air from the hot and

cold aisles. The addition of a containment systemwill mitigate this problem and

improve efficiency.

Another common problem is so-called “bypass air” within the cabinets

themselves. A simple solution is the installation of blanking panels in the un-

used spaces in the racks to prevent the warm air from the rear being drawn for-

ward within the cabinet.

Amethod to improve cooling efficiency is

to raise the air temperature from the tradi-

tional 68 to 70 degrees Fahrenheit to 75 to

78 degrees Fahrenheit. In 2008, the Ameri-

can Society of Heating, Refrigerating and

Air-Conditioning Engineers (ASHRAE)

recognized this and released its 9.9 stan-

dard in 2008, which stated that IT equip-

ment could safely operate at up to 80.6

degrees Fahrenheit.

It is imperative that the temperature is raised slowly and that all equipment

intake air temperatures are constantly monitored to make sure that none ex-

ceed the maximum allowable temperature limits.

FREE COOLING

No discussion of cooling efficiency would be complete without including so-

called “free cooling,” also known as economizers:

DAir Side Economizers: The underlying concept of using air economizers is rel-

atively simple—just open the windowwhen it is cooler outside than inside.

However, the implementation in a data center is not quite that easy. The temper-

ature and humidity must be controlled, and any sudden changes in either must

be avoided. Air side economizers cannot just bring in cooler outside air and ex-



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EFFICIENCY

The underlyingconcept of using aireconomizers isrelatively simple—just open the windowwhen it is cooler out-side than inside.

haust the warm air to reduce the mechanical cooling requirements, they also

need to filter the outside air and provide a range of humidity control without

expending more compressor energy than necessary.

DWater Side Economizers: Themore popular “water side” fluid cooler systems

are incorporated with control valves into the warmed return side of the chilled

water—or glycol—loop, which can then be re-routed through a fluid-to-air heat

exchanger before coming back to the chiller plant. This allows partial or total

“free cooling” by either reducing or totally

eliminating the need for the chiller com-

pressors to run on cold days.

It should be noted that a significant por-

tion of larger data centers use evaporative

cooling systems. Although they are more

energy-efficient than air cooled systems,

they do use a significant amount of water.

Some large data centers use millions of

gallons per month, but in all The Green Grid and EPAmetrics, the issue of

water usage is ignored.Water shortages may become a critical factor in the

coming years. Some of the newer large data centers have begun to incorporate

water recycling into their cooling systems.

Others are located where water is readily available and unconstrained—at

least for the present. Although the issue of water usage is not just a data center

problem—many energy-intensive industries also use huge amounts of water for

cooling, including the utility power plants themselves— it would seem disin-

genuous to speak of data center efficiency metrics without anymention of

water usage. �



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Some of the newerlarge data centershave begun to incor-porate water recyclinginto their coolingsystems.

UPS and Power Distribution Efficiency

conditioned and reliable power is taken for granted in data centers. Up

until recently, the efficiency of an uninterruptible power supply was almost a

side note in many purchasing decisions.With the rising cost of energy, the

focus has now included efficiency when reviewing UPS potential purchases for

new data centers.

UPS has a range of specifications that are sometimes misinterpreted and con-

fused with actual energy efficiency. In order to understand and calculate a

UPS’s true efficiency, let’s examine each term and understand its inherent rela-

tionship with the others:

D Voltage: Three phase/single phase voltage in the U.S. and North America is

normally specified as 480/277V or 208/120V and 400/230V for Europe. Also im-

portant to note is that 400/230V is representational composite of various Euro-

pean and Asian systems, which include 380/220V 400/230V and 415/240V. In

addition, there are also 600V systems, used in some Canadian andU.S. facilities.

D KVA: Kilo Volt Amps, also known as “apparent power.” This represents volts

x amps expressed in thousands. For example:

For single phase only: 120V x 50A = 6,000 VA = 6 KVA.

For three-phase power: 208V x 50A x 1.732 = 18,012 VA = 18 KVA

(note: 1.732 is the square root of 3)

D KW: Kilowatts, also known as “actual power” or “heat value.” This is calcu-

lated bymultiplying KVA x power factor. For example, 18 KVA at 0.9 power fac-

tor = 16.2 KW



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UPS AND POWERDISTRIBUTION

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D Power Factor: Although a simplified explanation, power factor (PF) repre-

sents the difference—expressed as a decimal multiplier such as 0.9—between

KVA, which is “apparent power,” and KW “actual power,” or “heat value” for

non-linear reactive loads, such as computer power supplies, which are unlike

pure “resistive” loads, such as incandescent bulbs or heaters.

D Power Factor Corrected: Also known as PFC, power factor corrected repre-

sents a non-linear reactive device’s ability to compensate and “improve” its

power factor to approach that of a “pure” non-reactive load. For example, older

computer power supplies typically had a 0.8 input power factor. This meant

that the UPS had to provide the equipment with 1,000 VA to deliver 800 watts.

Most modern computer power supplies are now “power factor corrected” at

0.95 or better, meaning that the UPS only needs to provide approximately 842

VA to deliver 800 watts.

D Input Power Factor: This is important to the upstream equipment in the

power chain. Like older computer power supplies, older UPSes were rated at

0.8 PF and required more “apparent power” (KVA) to deliver “actual power”

(KW). For example, an older UPS 100 KVAwith an “input power factor” of 0.8

would require approximately 125 KVA from the upstream equipment. Amod-

ern 100 KVAUPSwith an Input Power Factor of 0.95 would only require ap-

proximately 105 KVA.

DOutput Power Factor: Most uninterruptible power supplies today are offered

by different vendors with different output power factors, typically rated at 0.8,

0.9 and 1.0. This is a commonly misunderstood specification and represents the

real net power rating of the UPS and howmuch “actual power” it can deliver to

the IT load. For example, a 100 KVAUPSwith a 0.8 output power factor can

deliver only 80 KW. However, if it were rated at 0.9 PF, it could deliver 90 KW,

and at 1.0 it could deliver 100KW to the IT load. As you can see, this is espe-

cially important because most IT loads today are “power factor corrected” at



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0.95 or better. When evaluating different UPSes and their relative costs,

consider the output power rated in KW, not in KVA.

MORE ABOUT EFFICIENCY

UPS energy efficiency can only be correctly calculated in KW—not KVA.

Do not be misled by anyone calculating in KVA or citing power factors as effi-

ciency. It represents the amount of actual power delivered—in KW—of the

UPS output, divided by the input power in KW.

For example, a UPSwith a 91 KWmeasured output with a 100KW actual

input = 91% efficiency. This specification or measurement is usually based on

the UPS operating with a fully charged battery.

In effect, the other 9 KW are UPS losses and are converted to heat. Not all

UPSes will report their input and output in KW—somemay only report KVA.

To get a valid measurement a “true” power meter, which will measure KVA,

KW and PF is required.

The biggest gray area by UPS vendors that promote their efficiency claims

is citing just a single number —such as 91%—when providing a UPS efficiency

specification. Although the claim of 91% efficiency may be true, it is usually

only valid at or near full load.

This is not really howmost uninterruptible power supplies operate. In many

cases, a UPSwill typically operate at 40% or less than its rated capacity. This is

especially true for N+1 or 2N redundant UPS Installations. It is extremely im-

portant to get full disclosure of the efficiency curve over the entire load curve—

10% to 100%—from the manufacturer.

Because the UPS is an essential component in the computing power chain,

the EPA is in the process of establishing an Energy Star standard for the UPS

at this time.

Older UPSes have extremely poor efficiency when operating in their lower

ranges. In some cases, they are only 60% to 70% efficient when at a 30% load.

In contrast, a modern UPSwill have 85% to 90% efficiency rating at only 30%



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http://www.energystar.gov/index.cfm?c=new_specs.uninterruptible_power_supplies

of full load and 90% to 95% over the higher load range.

Several manufacturers now offer modular UPS systems, which offer several

advantages. They generally lower the initial capital costs because the UPS can

be purchased with a lower initial capacity. It also allows the UPS to operate at a

higher utilization factor, which allows for more efficient operation.

If your UPS is five years old or older, it may pay to review its actual operating

range and efficiency. The capital cost of a newUPSmay have a fairly quick cost

recovery if you can have an overall 15% to 20% gain in UPS efficiency.

One of the other areas that can affect electrical efficiency is the voltage that is

used to feed the UPS and to distribute to the floor level power distribution units

(PDUs), as well as the IT equipment itself.

Generally speaking, it is preferable to op-

erate at the highest possible voltage, start-

ing at the UPS.

Also, it is more efficient, both from a

distribution point and from the IT equip-

ment perspective, to operate at 208V in-

stead of 120V. Virtually all modern power

supplies are universal and can operate from 100V to 250V, but they are 3% to 5%

more efficient at 208V to 240V than at 120V. If possible, it is best to bring three-

phase 208V power to every rack because power densities are increasing, and it

is less costly to install the extra two conductors initially than to rewire later.

This will allow three times the power for very little extra up-front cost.

A final note about the IT load itself: Check and inventory all the IT equip-

ment. It has been shown repeatedly that there is a lot of equipment still plugged

in and drawing power, but no one knows who owns it or what it does. The best

way to improve data center efficiency is simply to turn off and remove all the

equipment that no longer is needed or producing useful work. �



SERVER EFFICIENCY




EFFICIENCY

If your UPS is fiveyears old or older,it may pay to reviewits actual operatingrange and efficiency.

Julius Neudorfer is

chief technical officer and

a founding principal of

Hawthorne, N.Y.-based

North American Access Technologies

Inc., which specializes in analyzing,

designing, implementing and managing

technology projects. He has designed

and managed communications and data

center projects for both commercial

clients and government customers since

1987. Contact him at [email protected].

Frank J. Ohlhorst

is an award-winning

technology journalist,

professional speaker and

IT business consultant with more than

25 years of experience in the technology

arena. Ohlhorst has worked with all

major technologies and accomplished

several high-end integration projects

in a range of industries, including

federal and local governments as

well as Fortune 500 enterprises and

small businesses. Contact him at

[email protected].



SERVER EFFICIENCY



Cathleen GagneEditorial Director

[email protected]

Matt StansberryExecutive Editor

[email protected]

Christine CasatelliEditor

[email protected]

Marty MooreCopy Editor

[email protected]

Linda KouryArt Director of Digital Content

[email protected]

Jonathan BrownPublisher

[email protected]

Peter LarkinSenior Director of [email protected]

TechTarget275 Grove Street, Newton, MA 02466

www.techtarget.com

© 2010 TechTarget Inc. No part of this publica-tion may be transmitted or reproduced in anyform or by any means without written permis-sion from the publisher. For permissions orreprint information, contact Renee Cormier,Director of Product Management, Data CenterMedia, TechTarget ([email protected]).

ABOUT THEAUTHORS

mailto:[email protected]









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