Harmonizing Global Metrics for Data Center Energy Efficiency
データセンタのエネルギー効率に関する指標の世界協調について

Global Taskforce Reaches Agreement on Measurement Protocols for GEC, ERF, and CUE –Continues Discussion of Additional Energy Efficiency Metrics
October 2, 2012
世界的タスクフォースはGEC、ERF、CUEの測定方法について合意に達するとともに、追加的なエネルギー効率指標に関する議論を継続する
2012年10月2日

The data center has become an increasingly important part of most business operations in the twentyfirst century. With escalating demand and rising energy prices, it is essential for the owners andoperators of these mission critical facilities to assess and improve their performance with energy
efficiency and Greenhouse Gas (GHG) Emission metrics. However, even with the global presence ofmany companies, these metrics are often not applied consistently at a global level.
To address these inconsistencies, a group of global leaders has been meeting regularly to agree on
standard approaches and reporting conventions for key energy efficiency and GHG emission metrics.
These organizations are: U.S. Department of Energy’s Advanced Manufacturing Office and Federal
Energy Management Programs, U.S. Environmental Protection Agency’s ENERGY STAR Program,
European Commission Joint Research Center Data Centers Code of Conduct, Japan’s Ministry of
Economy, Trade and Industry, Japan’s Green IT Promotion Council, and The Green Grid.
A joint statement in February 2011 highlighted the agreement reached specific to measurement
protocols for PUE and further goals and guiding principles for collaboration. Since then, this work
has been expanded to provide measurement guidelines and next steps for three additional metrics;
Green Energy Coefficient (GEC), Energy Reuse Factor (ERF), and Carbon Usage Effectiveness(CUE). This current document reflects agreements reached as of October 2, 2012. The group intends
to continue collaboration as an ongoing effort to improve Data Center Energy efficiency and GHG
Emission efficiencies.
【仮訳】21世紀において、データセンタは事業運営において非常に重要な役割を担うものとなった。
需要が増加しエネルギー価格が上昇するなかで、重要な役割を担うこれらの設備の所有者や管理者にとって、エネルギー効率と温室効果ガス排出の指標を利用して設備の性能を評価し向上させることは必要不可欠である。しかしながら、多数の世界的企業が存在するにもかかわらず、多くの場合、これらの指標は世界レベルでは一貫した形で利用されていない。
この一貫性がない状況に対して、データセンタ業界における世界的なリーダーが、主要なエネルギ
ー効率と温室効果ガス排出の指標の標準的測定方法と報告方法の合意を目指して、チームを作り定期的に会議を開催してきた。参加組織は、米国エネルギー庁の「先進製造技術局と連邦エネルギー
管理プログラム」、米国環境保護庁の「エネルギースター・プログラム」、欧州委員会共同研究センターの「データセンター・コードオブコンダクト（行動規範）」、日本の経済産業省とグリーン
IT推進協議会、そしてグリーングリッドである。
2011年2月の合同声明では、PUE測定基準に関する合意と、さらなる協調に向けた目標と基本理念を強調した。それ以降、このチームは、３つの追加的指標―グリーンエネルギー利用率（GEC）、エHarmonizing Global Metrics for Data Center Energy Efficiency

Page 1

ネルギー再利用係数(ERF)とカーボン利用効率 (CUE)の測定ガイドラインと今後の展開を提供す
るところまで到達した。本文書は2012年10月2日の会議での決定事項を反映している。このチームは、
データセンタのエネルギー効率の向上と温室効果ガス排出係数の改善に向けた継続的な取り組みに対し、今後も協調を続ける予定である。

Goal
Share global lessons and practices with an objective of arriving at a set of metrics, indices, andmeasurement protocols which can be formally endorsed or adopted by each participant organization
to improve data center energy efficiency and GHG Emissions globally. This includes the following
specific goals:
1. Identify an initial set of metrics
2. Define each metric
3. Define the process for measurement of each metric4. Establish on-going dialog for development of additional metrics【仮訳】目標データセンタのエネルギー効率と温室効果ガス排出を世界規模で改善するため、これまでの世界規模の経験と取り組みを共有し、各参加機関が公式に承認し導入することができる指標と測定基準を確立することを目標とする。特に、以下の具体的な目標を含むこととする：
1. 初期段階の指標の特定
2. 各指標の定義
3. 各指標の測定プロセスの定義
4. 追加指標の開発に向けた意見交換の場の設置

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Desired Outcomes
There are several desired outcomes of the Taskforce’s activities.
Outcome (1) – Effective energy efficiency metrics that measure the actual IT work output of the data
center compared to actual energy consumption. It is of note that in the process to define IT
work output, the following interim measurements are being defined and/or validated:
Outcome (1.a) – IT – Measure the potential IT work output compared to expected energy
consumption; and measure operational utilization of IT Equipment.
Outcome (1.b) – Data center facility and infrastructure – Measure the data center
infrastructure and efficiency (Power Usage Effectiveness - PUE)
Outcome (2) – Measure renewable energy technologies and re-use of energy to reduce carbon.
【仮訳】期待される成果
タスクフォースの活動では、以下のような成果をめざす：
成果(1) - 実際のエネルギー消費量に対する実際のデータセンタのIT機器の仕事量を測定する効果
的なエネルギー効率指標。IT機器の仕事量を定義する際、以下の中間測定方法が定義され、かつ/または有効である。
成果(1.a) - IT機器について： IT機器の定格エネルギー消費量に対する仕事能力を測定する。また、IT機器利用率を測定する。
成果(1.b) - データセンタの設備とインフラについて： データセンタのインフラ（付帯設備）の効率（PUE = Power Usage Effectiveness）を測定する。
成果(2) - 炭素排出量削減のため、再生可能エネルギーと再利用エネルギーの量を測定する。

Guiding Principles
It is recommended by all that the development of metrics to address Outcomes (1.a), (1.b), and (2),should form a holistic framework to help understand interactions among metrics. The Taskforce
recommends viewing the various data center efficiency metrics in a multi-parameter framework, suchas a spider chart. Viewing the metrics in a multi-parameter framework helps owners and operators
identify the effect of changes made to the data center specific to the various efficiency metrics. Thisapproach is further outlined in Appendix F. Along with the energy efficiency and GHG Emission
measurements and metrics, all should keep absolute values in the forefront of all decision making.
Attempting energy efficiency or GHG Emission programs should help to decrease the absoluteenergy use or GHG Emissions per unit.
The Taskforce has finalized discussions and agreed on the following:
Outcome (1.b) – It is recommended that data centers begin to measure PUE according to theseprinciples:

Harmonizing Global Metrics for Data Center Energy Efficiency

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PUE using source energy is the preferred energy efficiency metric. PUE is ameasurement of the total energy of the data center divided by the IT energy consumption

The industry should improve the IT measurement capabilities to ultimately enable taking
the measurement directly at the IT load (e.g. servers, storage, networking, etc.). The
recommendation is to measure the IT energy at the output of the PDU. At a minimum ITenergy measurements should be measured at the output of the UPS.



For a data center, total energy measurement should include all energy sources at the pointof utility handoff. Total energy should include all cooling, lighting, and support
infrastructure, in addition to IT load.



Additional detail on measurement guidelines have been added in Appendix A for PUE
measurements. The additional detail provides guidelines specific to equitablemeasurements of PUE with various designs; using multiple energy inputs (including
renewable energy), on-site generation, and re-use of energy.

【仮訳】ガイドライン
成果 (1.a) と(1.b), そして (2) に取り組むための指標の開発においては、それらの指標がどのように相互に関係しているかを理解するために、総合的な評価体系が形成されることが望ましい。タスクフ
ォースは、例えばスパイダーチャート（レーダーチャート）のようなマルチパラメーター体系を用
いて様々なデータセンタの効率指標を見ることを勧める。そうすることによって、データセンタ所
有者や事業者に、様々な効率指標に基づきデータセンタを改善することの効果を理解してもらうことができる。これについては附録Fに記述している。エネルギー効率と温室効果ガス排出の指標においては、全員が絶対量を基本とすることが望ましい。エネルギー効率の改善や温室効果ガス排出プ
ログラムの試みは、エネルギー消費や温室効果ガス排出の絶対量削減につながるべきである。
タスクフォースは以下のように議論をまとめ合意に達した：
成果 (1.b) –データセンタは 次のような原則によるPUE測定を始めることが推奨される。


ソースエネルギーを用いたPUEが、エネルギー効率を測る指標として望ましい。なお、PUEはデータセンタの全消費エネルギーをIT機器の消費エネルギーで割ったものである。



最終的にIT機器（サーバ、ストレージ、ネットワーク等）の負荷の直接測定を可能にするため、業界はIT機器のエネルギー測定能力を改善すべきである。IT機器の消費エネルギーの測定を
PDUの出力にて実施することが推奨される。少なくとも、IT機器の消費エネルギーの測定はUPSの出力にて行うべきである。



データセンタにおいては、全消費エネルギーの測定はutility handoff（ユーティリティの責任転
換箇所；施設と外部の境界）における全エネルギー源を含めて行うべきである。全消費エネル
ギーは、IT機器の消費エネルギーに加え空調や照明、他のインフラの消費エネルギーを含むべきである。

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

測定ガイドラインに関する付加的な詳細が、下記のPUE測定に関する附録A に付け加えられている。この付加的な詳細は、異なる種類のエネルギー（再生可能なエネルギーを含む）の利用
やオンサイト発電、エネルギーの再利用など、多様な事例におけるPUEの公平な測定方法に関して、具体的なガイドラインを提供する。

Outcome (2) – It is recommended that data centers begin to measure GEC, ERF, and CUE
according to these principles:

GEC is a metric that quantifies the portion of a facility’s energy that comes from green
sources. GEC is computed as the green energy consumed by the data center (kWh)divided by total energy consumed by the data center (kWh). For the purposes of GEC,
Green energy is defined as any form of renewable energy for which the data center owns
the rights to the green energy certificate or renewable energy certificate, as defined by alocal/regional authority. This definition is discussed in greater detail in Appendix C.
Total energy consumed at the data center is the total source energy, calculated identicallyto the numerator of PUE.



ERF is a metric that identifies the portion of energy that is exported for reuse outside ofthe data center. ERF is computed as reuse energy divided by total energy consumed by
the data center. Reuse energy is measured as it exits the data center control volume see
Appendix D. Total energy consumed by the data center is the total source energy,
calculated identically to the numerator of PUE.



CUE is a metric that enables an assessment of the total GHG emissions of a data center,
relative to its IT energy consumption. CUE is computed as the total carbon dioxide
emission equivalents (CO2eq) from the energy consumption of the facility divided by the
total IT energy consumption, for data centers with electricity as the only energy source
this is mathematically equivalent to multiplying the PUE by the data center’s carbon
emission factor (CEF). These calculation approaches are further defined in Appendix E.

成果 (2) –データセンタは次のような原則によるGEC、ERF、CUEの測定を始めることが推奨される：


GEC はグリーンエネルギーを利用した電力使用割合を表す指標である。GEC は、データセンタで消費されるグリーンエネルギー(kWh)をデータセンタで消費される全エネルギー(kWh)で割ることにより算定される。GEC で対象とするグリーンエネルギーは、地方/
各国の当局によって定義され、データセンタがグリーンエネルギー証明書または再生可能エネルギー証明書の版権を所有する再生可能エネルギーと定義される。これについては附録 C にさらに詳しく記述している。データセンタの全エネルギー消費量は全ソース
エネルギーであり、PUE の分子と同一である。



ERF はデータセンタ外で再利用するために取り出されるエネルギー量を明確にする指標である。ERF は再利用エネルギーをデータセンタの全消費エネルギーで割ることにより算定する。再利用エネルギーはデータセンタのコントロールボリュームから外部に出る

Harmonizing Global Metrics for Data Center Energy Efficiency

Page 5場所で測定する（附録 D 参照）。データセンタの全エネルギー消費量は、PUE の分子と同様に計算された、全ソースエネルギーである。


CUE はデータセンタの IT エネルギー消費に対する温室効果ガス排出量を測ることができる指標である。CUE はデータセンタ全体の二酸化炭素排出量（CO2eq）を全体の IT エ
ネルギー消費量で割ったものとして算定される。データセンタが電力のみを使用する場
合は、CUE はデータセンタの炭素排出係数（CEF）と PUE の積と数学的に同等である。
附録 E にさらに詳しい算出方法について記述している。

Progress to Date and Next Steps
Desired Outcomes:
Outcome (1) – Measure the actual IT work output of the data center compared to actual energy
consumption. At this time the Taskforce is primarily focusing on Outcome (1.a).
Outcome (1.a) – IT – Measure the potential IT work output compared to expected energy
consumption; and measure operational utilization of IT Equipment. Over this past
year the Taskforce has reviewed the following metrics and continues to evaluate theirapplicability through industry trials:
IT Equipment Efficiency (ITEE) & IT Equipment Usage (ITEU). For further details see thepublished GIPC material: http://www.greenit-pc.jp/e/topics/release/100316_e.html
Data Center Energy Productivity (DCeP) Proxies, Bits per kWh Proxy, CPU Utilization Proxies, OSinstance Proxy. For further details see The Green Grid published material: http://www.thegreengrid.org/en/Global/Content/whitepapers/Productivity%20Proxy%20Proposals%20Feedback%20Interim%20Results【仮訳】これまでの進展と今後の展開期待される成果に関して：
成果（1）－実際のエネルギー消費量と比較した、実際のデータセンタのIT機器の仕事量を測定する。
現時点ではタスクフォースは主として成果 (1.a) に集中している。
成果（1.a）－IT機器について： IT機器の定格エネルギー消費量に対する定格仕事能力を測定する。
また、IT機器利用率も測定する。過去1年の間、タスクフォースは以下の指標を検討し、業界での試行を通じてそれらの指標の適用性に対する評価を続けている。
IT機器電力効率（ITEE）とIT機器利用率（ITEU）
さらに詳しい内容はGIPCの資料を参照。

Harmonizing Global Metrics for Data Center Energy Efficiency

Page 6 http://www.greenit-pc.jp/e/topics/release/100316_e.html
データセンターエネルギー生産性 (Data Center Energy Productivity, DCeP) プロキシ、Bits per kWh プ
ロキシ、CPU稼働率 (CPU Utilization) プロキシ、OS instance プロキシ。詳細はグリーングリッドによる資料を参照

http://www.thegreengrid.org/en/Global/Content/whitepapers/Productivity%20Proxy%20Proposals%20Feedback%20Interim%20Results
Outcome (1.b) – Data center facility and infrastructure – Measure the data center infrastructure andefficiency (PUE). With the above revised guiding principles, there are no further
outstanding PUE related items for discussion at this time.
Outcome (2) – Measure renewable energy technologies and re-use of energy to reduce carbon. With
the above revised guiding principles, there are no further outstanding items fordiscussion at this time.
成果 (1.b) - データセンタの設備とインフラについて： データセンタの付帯設備電力効率（PUE）を測定する。上記の改定ガイドラインを作成した結果、PUEに関する顕著な論点は現在のところ存在しない。
成果 (2) - 炭素排出量削減のため、再生可能エネルギーとエネルギーの再利用量を測定する。上記の改定ガイドラインを作成した結果、顕著な論点は現在のところ存在しない。

This guidance is meant to provide a status update for the Taskforce’s desired outcomes and to help
drive a common understanding of energy efficiency metrics. With continued dialog and additional
input by a variety of stakeholders, this guidance will be refined and expanded to maximize its impact
on both energy consumption and operational efficiency. There is significant interest and work among
the bodies represented to proceed with globally accepted metrics and measurement protocols,
providing guidance to range from minimum recommendations to best practices.
The Taskforce has met in the U.S., Italy, and Japan and has recently celebrated three years ofcollaboration. The Taskforce has confirmed to continue the discussion and collaboration around these
metrics toward global harmonization of metrics for data center energy efficiency.
このガイダンスは、タスクフォースの期待する成果に関する状況を更新し、エネルギー効率指標の共通認識を推進するためのものである。本ガイダンスは、エネルギー消費と運用効率における効果を最大にするために、継続的な議論と様々な利害関係者からの追加インプットによりさらに整備、拡充される。最低限の推奨からベストプラクティスまで幅の広いガイダンスを実施しながら世界的に受け入れられる指標や測定基準の整備を進めるということに、参加各機関は極めて高い関心を持って取り組んでいる。
タスクフォースはアメリカ、イタリア、日本にて会議を開催し、最近活動の開始から3年の節目を迎えた。タスクフォースは今後もデータセンタのエネルギー効率に関する世界指標の協調に向けて、指標に関する議論と協同を続けることを確認した。

Participating Organizations

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Each organization is represented on the Taskforce, which convenes regularly to advance the progressof the group. A full group of participants from each organization continues to meet in person every 6
to 12 months, as the Taskforce feels it is appropriate based on progress.
参加機関
本会議に参加した全ての機関によってタスクフォースが構成されており、このグループは状況を進展させるために定期的に会議を開催している。各機関からの全ての参加者は、進捗に応じてグループが適当だと判断した時期に6ヶ月から12ヶ月毎に顔を合わせ、会議の開催を継続する。

For further details, please contact:
 The Green Grid: gdcmetrics@lists.thegreengrid.org
 U.S. Department of Energy: http://www1.eere.energy.gov/industry/datacenters/contacts.html
 U.S. Environmental Protection Agency’s ENERGY STAR Program:
www.energystar.gov/datacenters European Commission – Joint Research Centre:
http://re.jrc.ec.europa.eu/energyefficiency/html/standby_initiative_data_centers.htm
 Ministry of Economy, Trade, and Industry: http://www.meti.go.jp/english/index.html
 Green IT Promotion Council: http://www.greenit-pc.jp

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List of Appendices
Appendix A – Power Usage Effectiveness (PUE) Measurement Details ............................................ 10
Appendix B – Power Usage Effectiveness (PUE) Illustrative Calculation Examples ......................... 14
Appendix C – Green Energy Coefficient (GEC) Measurement Details .............................................. 17
Appendix D – Energy Reuse Factor (ERF) Measurement Details ...................................................... 21
Appendix E – Carbon Usage Effectiveness (CUE) Measurement Details .......................................... 23
Appendix F – Holistic Framework....................................................................................................... 28

Harmonizing Global Metrics for Data Center Energy Efficiency

Page 9Appendix A – Power Usage Effectiveness (PUE) Measurement Details
The seemingly simple concept of PUE requires additional detail to ensure that it is appliedconsistently across data centers. Consistent calculations of PUE facilitate communication of
performance among data center owners and operators.
PUE is computed as follows:
PUE = Total Data Center Source Energy
IT Source Energy
The following clarifications apply to the PUE calculation:Total Energy (Data Center Boundary) – Total Energy should be measured at the point ofutility hand off to the data center. This may include measurements of electricity, chilledwater, natural gas, fuel oil, or other purchases made from a utility. All measurements should
be made from the point where the energy is purchased. In the case where natural gas ispurchased to produce chilled water or electricity, measurement shall occur of the natural gas
purchase and not of the secondary energy it produces. Electricity from renewable energy
sources should be included in the total energy and assigned the same source factor as gridelectricity.
o Consistent Units – All energy shall be reported using the same units, and therecommended unit of measure shall be kWh. Standard thermal conversion factors
shall be used to convert to kWh (e.g. 1 kWh = 3.412 kBtu; 1 GJ = 278 kWh).



IT Energy – IT Energy shall be measured in kWh. The recommendation is to measure the IT
energy at the output of the PDU. At a minimum IT Energy should be measured at the outputof the UPS.



Source Energy – Source Energy is a means of assessing the total primary energy use or fuelconsumption at a data center. The purpose of source energy is to ensure that data centers thatpurchase different forms of energy (electricity, natural gas, chilled water) can compare their
total consumption equitably. For example, if one data center purchases chilled water from a
local utility company while another data center uses electricity to produce chilled water
onsite, a factor is required to put the two utility bills in common units for comparison. Thisfactor is called a source energy factor, and it is a factor to reflect the total fuel consumption.
Because the majority of data centers operate with 100% electricity, this global group
recommends source energy factors that are weighted with respect to electricity. In otherwords, after source factors are developed for each fuel, they are each expressed relative to thesource factor for electricity. This convention allows for any electric purchases to be
multiplied by a factor of one. Purchases of other fuels are multiplied by their respective
factors before being added to the total.
Weighted energy for each energy type = (Annual energy use * source energy weighting
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The source energy factor is inherently a regional factor because the amount of fuel needed to
produce one unit of electricity (or chilled water) will depend on the predominant method ofelectric (or chilled water) generation in the specific country. Some countries have publishedvalues for these conversion factors (such as the EPA ENERGY STAR Program). However,to enable a fair global comparison, this global group recommends that standard, global
factors be applied. Global factors represent average values of factors from different regions.
While the global factors are recommended for comparisons across different regions of theworld, regional factors may be applied for greater accuracy of comparison within a specificregion.
The global average source energy weighting factors shall be:
Energy Type
Weighting Factor
Electricity
1.0
Natural gas
0.35
Fuel oil
0.35
Other fuels
0.35
District chilled water
0.4
District hot water
0.4
District steam
0.4
Table 1: Global average source energy weighting factors
To express Total Source Energy, each fuel should first be converted into a single common
unit (kWh); then each fuel should be multiplied by its weighting factor; finally, the sourceenergy for all fuels can be summed together.


On-Site Electric Generation – To enable equitable PUE calculations in data center designs
that operate on-site electric generation two topics need to be explained:o IT Source Energy Conversion Factor
 To ensure the PUE calculations for a design including on-site electric
generation and a design excluding on-site electric generation are equitable,
the taskforce has introduced the IT Source Energy Factor. The IT Source
Energy Factor enables the data center owner / operator to include theefficiencies of generating chilled water (as in all calculations for PUE), but
exclude the efficiencies of generating electricity (as in all calculations for
PUE). PUE is not a metric to identify the efficiencies of how electricity isbrought to the data center, it is a metric to identify how efficient theelectricity is used from the data center control volume to the IT Equipment.

Harmonizing Global Metrics for Data Center Energy Efficiency

Page 11

Example A: Data center with electric and natural gas (Co-generation) purchaseo Cogeneration Input Fuel Assumption
 This taskforce has adopted the assumption that 67% of a cogeneration plants’
input fuel is allocated to the primary form of generation (electricity in theprovided example) and respectively 33% of the primary input fuel is allocatedto the secondary form of generation (chilled water in the provided example).
 This assumption is based on a similar steam based cogeneration study fromthe U.S. Environmental Protection Agency’s Energy Star Program.
Differences do exist between the two scenarios, but to solidify themethodology of calculating PUE and to drive consistent and equitablecalculations for all design types, this taskforce is proceeding with therecommendation to adopt this approach. As further data specific tocogeneration examples are provided, the data will be taken into consideration.
Provided there is a material change in calculations, the taskforce will consider
updating the recommendations specific to this assumption.
 Stakeholder feedback is welcome and encouraged to continue the adoption,
consistent communication, and equitable calculations for PUE in an effort toimprove energy efficiency.
Energy Re-use – Energy that is re-used shall not be subtracted from the total energy use of
the data center.
o If the energy is reused within the datacenter, the value of the reused energy will
already be contained within the PUE calculation and needs no special consideration.
An example will be reusing waste heat to warm a battery space in a cool climate. The
PUE would generally be lower because the HVAC system does not have to add as

Harmonizing Global Metrics for Data Center Energy Efficiency

Page 12much energy to heat that battery space, thereby reducing the PUE when energy ismeasured and PUE calculated.
o If the energy is reused outside the data center (e.g. re-using heat to warm a lab that is
not part of the data center), the PUE of the data center is not affected. While the effort
to conserve energy is laudable, it cannot be accounted for in the calculation of thedata center PUE because it does not lower the actual total energy need of the data
center.


Measuring PUE in a Mixed-use Buildingo The definition of a Mixed-use Building is a facility that has a data center and services
not associated with the data center. As an example a Sales team or Marketing teamare also housed within a building, but have no direct support responsibilities for thedata center.
o The method for calculating PUE in a mixed use building is the same method for
calculating PUE in a dedicated data center except for some ancillary energy loads thatcan be excluded*: Energy required for shared support spaces: (ancillary energy loads)
 Shared offices
 Shared labs
 Shared cubicles
 Shared conference rooms Shared elevators
 Shared lobbies
 Shared Kitchens / break rooms* When excluding any ancillary energy loads this should be declared whenreporting PUE.
 The shared elevator is one example to illustrate the rationale for the above
noted exceptions. A data center can be a small portion of one floor located on
one level of a multistory building. The data center is located on the 5 th floorof a 10 story building. The 5th floor also is also mixed-use with manybusiness services and a data center. The effort to implement energy
measurements on the shared elevator and the effort to try to quantify how
much of that energy should be allocated to the data center traffic on the 5 thfloor is believed to be a point of diminishing returns. The proportional load
for the elevator is insignificant in the PUE calculation.
 Energy consumption of all dedicated space is to be included. As an example
if there are offices or cubicles that are dedicated to the data center operations,the energy consumption should be included. Provided the above direction isfollowed, PUE reporting of data centers within mixed-use buildings follow
the same nomenclature as PUE reporting of dedicated data centers.

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Appendix B – Power Usage Effectiveness (PUE) Illustrative Calculation Examples
The following illustrative examples have been provided to demonstrate a few data center designs andthe corresponding approach to calculate PUE by the above recommendations:

Example B – Data center with all electric purchaseHarmonizing Global Metrics for Data Center Energy Efficiency

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

Example C – Data center with electric and chilled water purchaseExample D – Data center with natural gas purchaseHarmonizing Global Metrics for Data Center Energy Efficiency

Page 15



Example E – Data center with electric and natural gas purchaseHarmonizing Global Metrics for Data Center Energy Efficiency

Page 16

Appendix C – Green Energy Coefficient (GEC) Measurement Details
Conceptually, GEC is a simple metric: the percent of energy that is green.
Complexity arises because there are regional and local differences in the definition of renewable /green energy. These regional differences may occur due to the different types of renewable energythat are prevalent, and due to the market for green energy products in each country. This task force
does not attempt to reconcile regional differences.
Rather, this task force recognizes green energy as any energy for which the data center owns thelegal right to the environmental attributes of green/renewable generation. These legal rights are
regionally recognized as Green Energy Certificates, Renewable Energy Certificates, and other similar
products. Due to regional differences, this Taskforce recommends all public reporting of GEC
include the source issuer of the certificates. Any energy for which the data center owns these rights is
considered green for the purposes of this metric. This would include retired Green Energy
Certificates, which are no longer a commodity to be traded and are possessions of the last owner or
the green certificate system administrator.
The following table contains a number of authorities recognized by this Task Force as defining or
issuing the equivalent of a Green Energy Certificate as described herein. This list is notcomprehensive and as other regional bodies emerge that issue and track green certificates, thatenergy should also be counted as green for the purposes of this metric.
Region Regional Authority / Issuer(s)Link
http://www.aibnet.org/portal/page/portal/AIB_HOME/EECS/Fact_Sheets (See Fact Sheet 4)
http://www.decc.gov.uk/en/content/cms/meeting_energy/renewable_ener/renew_obs/renew_obs.aspx

E.U.

Association of Issuing Bodies
Department of Energy andClimate Change

Japan

The Green Energy Certification
Centerhttp://eneken.ieej.or.jp/greenpower/eng/index.htm

U.S.A

U.S. EPA Green PowerPartnershipGreen-e

http://www.epa.gov/greenpower
http://www.green-e.org/

Table 2: Authorities defining or issuing the equivalent of a Green Energy Certificate
Given this definition of green energy, GEC is computed as follows:
GEC = Green energy used by the data center
Total Data Center Source Energy
GEC has a maximum value of 1.0, indicating 100% of the total energy used by the data center isgreen energy as defined above. Note that for the purposes of this calculation, the total source energy
Harmonizing Global Metrics for Data Center Energy Efficiency

Page 17consumed at the data center is identical to the numerator of PUE. As with PUE, all energy shall bereported using the same units, and the recommended unit of measure shall be kWh. Standard thermal
conversion factors shall be used to convert to kWh (e.g. 1 kWh = 3.412 kBtu; 1 GJ = 278 kWh).
Finally, because the definition of green energy is based on legal ownership of the rights to theenvironmental benefits it is important to clarify that the location of energy source does not change
the calculation of the GEC. For example, a data center may have a solar panel on its roof togenerate power; if it sells the Green Energy Certificates associated with this power, then it cannot
claim any of that electricity as green. Conversely, a data center that receives electricity entirely
from a coal-fired plant may purchase Green Energy Certificates to off-set the entire electric use.
These certificates would count as Green Energy.
These concepts are illustrated in several examples, as follows.


Example F: Grid energy purchased without Green Energy Certificates: GEC = 0.00.

Power Station

Grid Power
distribution

Utility meter

No Purchased Green Energy Certificates

Example G: Green Energy Certificates purchased and retired for 20% of
the energy used by the DC: GEC = 0.20

Power Station

Grid Power
distribution

Utility meter

DC Purchased Green Energy Certificates for
20% of energy used.

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

Example H: Green Energy Certificates for locally generated green
energy are retired by the DC: GEC = 0.10.

90 GWhPower Station

Grid Power
distribution

Utility meter

10 GWhDirect Gen
Meter
Green Energy Certificates NOT sold to 3 rd party.
DC has the right to use the Green Energy.
[No additional Certificates purchased.]
Renewable Energy
Generation



Example I: Locally generated energy sold to the utility, but Green
Energy Certificates retired by the DC: GEC = 0.20.

100 GWhPower Station

Grid Power
distribution

Utility meter

Green Energy Certificates
NOT sold to 3rd party.

20 GWhGreen
EnergyCertificate
Renewable Energy
Generation

Harmonizing Global Metrics for Data Center Energy Efficiency

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

Example J: The DC can retire Green Energy Certificates only for the energy it uses: GEC =1.00. Note that of the 130 GWh generated by renewable sources, the data center could sell 30
GWh worth of Green Energy Certificates without impacting its GEC of 1.00.

90 GWhPower Station

Grid Power
distribution

Utility meter

10 GWh10 GWh120 GWh

Direct Gen
Meter

Green Energy Certificates NOT sold to 3rd party.

Green
EnergyCertificate

Renewable Energy
Generation

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Appendix D – Energy Reuse Factor (ERF) Measurement Details
Increasingly in data centers, the energy from the data center is being reused in other parts of the
facility or campus with beneficial results. The benefits of energy reused within the data center are
captured by the PUE metric. Therefore the purpose of ERF is to incent reuse of energy outside of thedata center rather than rejection of energy. ERF is a metric that identifies the portion of energy that isexported for reuse outside of the data center. For example, reuse energy includes energy that isexported outside of the data center to another area within a mixed-use building or to another facility.
The basic equation for ERF is as follows:
ERF = Reuse energy outside of the data center
Total Data Center Source Energy
ERF will range from 0.0 to 1.0. The value at 0.0 means no energy is exported from the data center forreuse, while a value of 1.0 means all of the energy brought into the data center is reused outside ofthe data center.
With ERF, the concept of a control volume must be used. In simplest terms, the control volume is theimaginary boundary around the data center and its infrastructure support areas, such that whenenergy crosses this boundary, it needs to be accounted for. In Example K, the control volume isindicated by the dashed line.
To compute ERF, any energy used by the data center that leaves the control volume for use
elsewhere, is considered Reuse Energy. In Example K, the Reuse energy is denoted by (G), andshould not be confused with the reject energy (I). Total energy consumed by the data center is
identical to total energy as defined in PUE and includes all energy sources that enter the control
volume as denoted by (A). The source of the reuse energy must be known to enable equitablecalculations. The numerator is the re-use energy, also expressed in source energy. This captures allenergy that leaves the control volume. If energy leaves the control volume in the same form as itentered (e.g. extra chilled water that is passed along to another building), then the standard sourceenergy factors from Table 1 are used. However, if the energy that is reused is of a different form
because it was created within the data center, then the actual COP or efficiency of production must
be used to determine the correct factor.
Finally, while not captured within ERF it is important to consider the intrinsic value of the reuseenergy (e.g. hot air versus hot water) and how the energy is actually re-used after it leaves the control
volume. One should ensure that the process overhead to reuse the energy does not exceed theequivalent direct use of an energy source. The net total energy consumption should be less whenreusing energy.

Harmonizing Global Metrics for Data Center Energy Efficiency

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Example K: ERF showing the data center control volume.



Example L: ERF showing Electric & Chilled Water Purchase – Reuse from Chilled Water.

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Appendix E – Carbon Usage Effectiveness (CUE) Measurement Details
CUE is a metric to understand the carbon dioxide emission equivalents (CO2eq) from energy
associated with a data center. There are many commonly accepted international protocols thatprovide direction for quantifying total emissions of any type of facility. For a data center inparticular, CUE is a recommended metric because it evaluates the total GHG relative to the IT energy
consumption. Whereas an office building may be most interested in GHG per square foot, and an
automobile manufacturing plant may be interested in GHG per automobile produced, for the data
center, this Task Force recommends that GHG is evaluated relative to the IT energy consumption,using CUE.
Consistent with the desired outcomes of this Taskforce the scope of CUE includes the emissions
from energy consumption and excludes the emissions generated in the manufacturing of the IT
equipment, its subsequent shipping to the data center, the construction of the data center, etc. The
Taskforce considers the full life-cycle to be important to the overall sustainability of the industry but,for practical considerations, they are excluded from this metric. For now, CUE is specifically limited
to Scope 1 and Scope 2 emissions. For more on the definitions of Scope 1 and Scope 2 emissions,refer to: World Resources Institute and World Business Council for Sustainable Development(WBCSD), A Corporate Accounting and Reporting Standard (2004)
http://www.ghgprotocol.org/files/ghgp/public/ghg-protocol-revised.pdf, page 25.
To accomplish this complete inventory of emissions from all energy consumption, a data center must
include emissions from all energy sources (Note purchased carbon off-sets, green energy certificates,
and renewable energy certificates are excluded from CUE):
 Electricity
 District heat (chilled water, hot water, steam) Primary energy sources (natural gas, diesel, bio-gas, etc.)
 Renewable energy produced onsite
o If renewable energy is produced on-site (e.g. through solar or wind power), then theemissions of this energy depend on whether or not the Data Center owns the rights to
the green energy certificate or renewable energy certificate, as defined by alocal/regional authority. If these rights have been sold, then the emissions of thisenergy is equivalent to what the emissions would be with a conventional utility
purchase (e.g. grid-electric purchase). If the rights have not been sold, then theemissions for the renewable source are obtained from the references in Table 3.
For Data Centers with electricity as the only energy source, the recommended equation for CUE is:
CUE = CEF X PUE
Where:
 CEF is the Carbon Dioxide Emission Factor (kgCO2eq/kWh) of the site. For all electric data
centers the CEF is the single value obtained from Table 3.
 PUE is described in Appendix A.

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For Data Centers with multiple energy sources the recommended equation for CUE is:
Total C02 emissions caused by the Total Data Center Energy/ IT Equipment Energy
Where:
 Each type of energy source total C02 emissions are addedo IT Equipment Energy is defined as the Total kWh delivered to the IT Equipment
The units of the CUE metric are kilograms of carbon dioxide emission equivalents (kgCO2eq) per
kilowatt-hour (kWh) of IT energy consumption. CUE has an ideal value of 0.0, indicating that no
carbon use is associated with the data center’s operations.
Carbon emission factors should be obtained from the government’s published data for the region ofoperation for that year. All reports for CUE should disclose the source of the CEF used in thecalculation.
RegionE.U.

Japan
U.S.A.



Recommended Carbon Emission Data for Procured Energy
http://re.jrc.ec.europa.eu/energyefficiency/covenantofmayors/seap_guidelines_en-2.pdf
http://archive.defra.gov.uk/environment/business/reporting/pdf/100805-guidelines-ghgconversion-factors.pdf
http://ghg-santeikohyo.env.go.jp/files/calc/itiran.pdf
http://www.epa.gov/cleanenergy/documents/egridzips/eGRID2007V1_1_year05_Summar
yTables.pdf
http://www.energystar.gov/ia/business/evaluate_performance/Emissions_Support
ing_Doc.pdf?ac4e-840b
Table 3: Recommended Carbon Emission Data for Procured Energy

Example M: CUE with all Electric Energy Purchase Data Center

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CEF and CUE:
 In this example, let’s use US WECC CA as electric source to calculate CUE
 We can use EPA’s reference information to get CEF from:http://www.energystar.gov/ia/business/evaluate_performance/Emissions_Supporting_Doc.pd
f?d258-68cc
 Indirect Greenhouse Gas Emission Factors – Purchased Electricity













This WECC CA shows CEF as 90.8653 KgCO2e/MBtu.
o 1Btu= 0.293Wh
CEF will be 90.8653 / 0.293 = 310.12048 KgCO2e/MWh = 0.31012 KgCO2e/KWh
KgCO2e/KWh for Electricity = 0.31012
Electricity kWh: 1,633,333 kWh
Total Annual Energy: 1,633,333 kWh
Total Annual Emissions from Electricity = 1,633,333 *.31012 = 506,529.23
Total Annual Emissions from energy = 506,529.23
CEF = the total annual emissions from all sources divided by the total annual energy.
CEF = 506,529.23 / 1,633,333 = .31012
PUE = 1.63 in this example
CUE, as a function of CEF*PUE = 1.63*.31012 = .51

Harmonizing Global Metrics for Data Center Energy Efficiency

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Example N: CUE at a mixed energy purchase Data Center. (Electricity & Natural Gas)

CUE calculation:









In this example, let’s use US WECC CA as electric source to calculate CUE
We can use EPA’s reference information to get CEF from:http://www.energystar.gov/ia/business/evaluate_performance/Emissions_Supporting_Doc.pd
f?d258-68cc
Indirect Greenhouse Gas Emission Factors – Purchased Electricity

This WECC CA shows CEF as 90.8653 KgCO2e/MBtu.
1Btu= 0.293Wh
Then, Electric part of CEF will be 90.8653 / 0.293 = 310.12048 KgCO2e/MWh = 0.31012
KgCO2e/KWh

Harmonizing Global Metrics for Data Center Energy Efficiency

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













For the Natural Gas part, CEF can be found at this table of the same EPA link, as
53.200036KgCO2e/MBtu.
Direct Greenhouse Gas Emission Factors

Btu is required to covert Wh, 1Btu= 0.293Wh
Natural Gas part of CEF is 53.200036 / 0.293 = 181.5701 KgCO2e/MWh =0.18157KgCO2e/KWh
KgCO2e/KWh for Electricity = 0.31012
KgCO2e/KWh for Natural Gas = 0.18157
Electricity kWh: 843,750 kWh
Natural Gas kWh: 1,587,000 kWh
Total Annual Emissions from Electricity = 843,750*.31012 = 261,663.75
Total Annual Emissions from NG = 1,587,000*.18157 = 288,151.59
Total Annual Emissions from energy = 261,663.75 + 288,151.59 = 549,815.34
CUE, by definition, Total C02 emissions caused by the Total Data Center Energy/ Total kWhdelivered to the IT Equipment = 549,815.34/ (1,000,000) = .55

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Appendix F – Holistic Framework
A holistic framework approach enables awareness of the effect of changes made to the data center
specific to the various efficiency metrics. For example, one improvement at a data center that istargeted to improve a specific performance metric could have the result of making another metriclook worse. A holistic framework helps the operator keep in mind the effects on all metrics
simultaneously.
The Desired Outcomes section lists following three aspects of energy efficiency (or reduction ofcarbon emissions) of a data center. A Holistic framework is a way to grasp multiple metrics forenergy efficiency of a data center collectively:
Outcome (1.a) – IT – Measure the potential IT work output compared to expected energy
consumption; and measure operational utilization of IT Equipment.
Outcome (1.b) – Data center facility and infrastructure – Measure the data center
infrastructure and efficiency (Power Usage Effectiveness - PUE)
Outcome (2) – Measure renewable energy technologies and re-use of energy to reduce carbon.
To help understand and improve energy efficiency and GHG Emissions of data centers, it is useful toview all these aspects in a single chart. A spider or radar chart such as Figure 1 is a way to view thevarious metrics in a holistic framework. In the spider chart, metrics for all the Desired Outcomes(1.a), (1.b) and (2) are distributed to its axes to evaluate total energy efficiency of a data center.
As a holistic framework, each Desired Outcome [as listed at above; (1.a), (1.b) and (2)] should haveat least one, or more where applicable, metric in the spider chart. At this time the Taskforce has notprovided a recommendation for Desired Outcome 1.a. Once agreement is reached and arecommendation provided, the recommended metric(s) should be included into the holistic
framework. The number of metrics (axes) may vary depending on the selection of metrics chosen
by the data center operator. Figures 2 and Figures 3 shows variations of the spider chart with 4 and 5axes, respectively. In Figure 2, two metrics are adopted to Outcome 1.a. In Figure 3, three metrics are
adopted to Outcome 2. These metrics evaluate different aspects of Outcome 1a and Outcome 2.
Once the metrics are selected, the operator will also need to identify a start and end point for eachaxis. In some cases, there are theoretical maximum and minimum values (e.g. GEC can only range
from 0.0 to 1.0). In other cases, there are not clean maximum values (e.g. there is no maximum for
PUE). Therefore, the axis ends will have to be established based on target values or other estimates.
The selection of metrics and the selection of the axis end points both establish an implicit weighting
among the metrics, therefore care should be taken during this process.
【仮訳】Appendix F－総合的な評価体系
総合的な評価体系によって、多数の効率指標と紐づくデータセンタの改善への認識を深めることができる。例えば、ある特定の指標の改善に絞った特定の対策を実施すると、他の指標が悪くなってしまう可能性がある。総合的な評価体系によって、データセンタ事業者はすべての指標を同時に俯瞰することができるようになる。

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期待される成果の節では、データセンタのエネルギー効率（もしくは炭素排出削減）の 3 つの側面を示した。総合的な評価体系は、データセンタの複数のエネルギー効率指標をひとまとめにして認識する手段である。
成果(1.a)－IT 機器について： IT 機器の定格エネルギー消費量に対する仕事能力を測定する。
また、IT 機器利用率を測定する。
成果(1.b) －データセンタの設備とインフラについて： データセンタのインフラ（付帯設備）の効率（PUE = Power Usage Effectiveness）を測定する。
成果(2) －炭素排出量削減のため、再生可能エネルギーと再利用エネルギーの量を測定する。
データセンタのエネルギー効率と温室効果ガスの排出を理解し改善するためには、これらの観点す
べてをひとつの図でみることが有用である。図 1 のようなスパイダーチャート（またはレーダーチャート）は、総合的な評価体系において様々な指標を見るひとつの手法である。スパイダーチャー
ト（レーダーチャート）では、期待される成果(1.a) (1.b) (2)すべての指標が各軸に割り当てられ、
データセンタ全体のエネルギー効率を評価することができる。

総合的な評価体系では、期待される成果[上記の(1.a) (1.b) (2)]のそれぞれから最低一つ以上の指標がスパイダーチャート（レーダーチャート）に採用されなければいけない。現時点ではタスクフ
ォースは期待される成果 1.a の推奨指標は提供していない。合意に達し推奨指標が提供された際には、その指標が総合的評価体系に含められるべきである。指標（軸）の数はデータセンタ事業者が選択する指標によって異なってくるかもしれない。図 2 と図 3 はそれぞれ 4 つの軸、5 つの軸のスパイダーチャート（レーダーチャート）例を示している。図 2 では成果 1.a に対し 2 つの指標が採用されている。図 3 では３つの指標が成果 2 に採用されている。これらの指標は成果 1.a と成果 2のそれぞれ別の側面を評価している。事業者は、指標を選択したら次にそれぞれの軸の最小値と最大値を特定する必要がある。場合によっては、理論上の最大値と最小値が存在する（例：GEC は 0.0
から 1.0 の範囲のみである）。また、明白な最大値がない場合も存在する（例：PUE には最大値がない）。よって軸の最大値は目標値または他の見積もりに基づき定めなければならない。指標の最小値と最大値の選択は、指標間の潜在的な重みづけとなりうることから、これらの過程には注意が必要である。

Harmonizing Global Metrics for Data Center Energy Efficiency

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Outcome 1a[Axis 1] Outcome 1a
Measure operational utilization of IT
Equipment and the potential IT work
output compared to expectedenergy consumption[Axis 3] Outcome 2
Measure renewableenergy technologies andre-use of energy to
reduce carbon

Measured

Outcome 2

Outcome 1b[Axis 2] Outcome 1b
Measure the data center
infrastructure and theefficiency

Figure 1: A possible expression of “Holistic Framework”
Outcome 1a-1

Outcome 2

Outcome 1a

Outcome
1a-2

Outcome 2-3

OutcomeMe
Measured

Outcome 1b

Outcome 2-2(a) A spider chart with 4 axes

Outcome 2-1(b) A spider chart with 5 axes

Figure 2: Possible variations of a spider chart expression

Harmonizing Global Metrics for Data Center Energy Efficiency

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Outcome 1a-1

utcome 2

Outcome 1a

Outcome
1a-2

Outcome 2-3

Outcome 1b

Measured
Outcome 1b(a) A spider chart with 4 axes

Outcome 2-2

Outcome 2-1(b) A spider chart with 5 axes

Figure 3: Possible variations of a spider chart expression
The spider chart approach offers several benefits, by providing a combined visualization of all
metrics. In particular, by looking at a spider chart, a data center operator can see which metric isworst – this may be the metric with the greatest area for improvement. Another benefit is that the
spider chart lets an operator visualize the effects of an efficiency improvement on all metrics. The
goal is to move all metrics in the same direction toward increased efficiencies. Therefore, it would be
important after investing in changes at a data center to review the spider chart and confirm that all
metrics have improved. Finally, the spider chart can be used not only to plot current measured
performance, but also to plot target performance, so that progress towards a target can be tracked forall metrics at once.
【仮訳】すべての指標を統合的に可視化するスパイダーチャート（レーダーチャート）を利用する
ことには、いくつかの利点がある。データセンタ事業者は、スパイダーチャート（レーダーチャー
ト）を見ることによって、最も悪い指標がどれかを判別できる。そして、それは最も改善が必要な領域を示す可能性がある。さらに、事業者は、スパイダーチャート（レーダーチャート）によって、すべての指標の効率改善効果を可視化することができる。目標は、効率向上に向けた方向へすべての指標を動かすことである。よって、データセンタの改良後にスパイダーチャート（レーダーチャート）を見直し、すべての指標が改善されていることを確認することが重要である。最後に、スパ
イダーチャート（レーダーチャート）には現在の実測値だけでなく目標値も表示できる。そこで、目標達成に向けた変化を、全ての指標について同時に追跡することも可能である。

Harmonizing Global Metrics for Data Center Energy Efficiency

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