Using Data Centre Energy Benchmarking to Enhance ... Ed Ansett_neeconf.pdf · • Polymer,...

©2009 HP Confidential

Ed Ansett

Critical Facilities Services

HP Technology Consulting

24th May 2011

Using Data Centre Energy

Benchmarking to Enhance

Efficiency & Performance

Coypright HP 2011 - Subject to Change Without Notice HP Confidential

Background

• Data centres consume vast amounts of power

• Typically 30x an office of comparable size

• In 2008 data centres accounted for about 1.5% of US power consumption

• Server/storage capacity has roughly doubled since then

• Typical LEGACY data centre power efficiency (DCiE) stand at


Legacy Data Centre Issues

• Energy costs nowadays dominate OPEX and

TCO; yet when they were designed energy

efficiency was not a consideration

• Pressure on owners to measure, manage and

reduce energy efficiency

• Pressure to make data centres last longer

• Virtualization limited by power and cooling

available

• Built to the highest Tier Level - resulting in over-

engineering

• IT and Facilities misaligned


Technology Facility ParadoxProblem Definition

‘Technology is typically changed every 3 years. Data Centre lifetime is

typically15 - 20 years’

• Assuming a facility lifetime of 20 years: Tech refresh at yrs 3,6,9,12,15 & 18 –

Six refreshes

• Assuming a facility lifetime of 15 years: Tech refresh at yrs 3,6,9,12 - FOUR

refreshes


Future Generation Technology Refreshes

Moore’s law intact for next 10 years

• 130 nm → 90nm → 45nm → 30 nm → ?

Transistor density – 16G devices/chip by 2013

• Molecular devices ?

• Quantum devices ?

• Single electron transistors ?

Disk Media – Capacity doubles every 16 months

Memory – new materials

• Flash memory, Ferro-electric (FeRAM)

• Polymer, Magnetoresistive RAM (MRAM)

• Tunneling Magnetic Junction RAM (TMJ-RAM)

Guilder’s law

• Bandwidth doubles every 12-18 months

Nanotechnology

• Memristor - Fourth electronic circuitry element

• Real-time data analysis with low-cost, self-powered sensors

Higher Performance =>

COMPACTION =>

• Higher power density

• Automation

• Optimised Infrastructure

• Dynamic resource allocation


Data Centre Environmental Performance Standards, Guidelines & Metrics - Gaining Acceptance

• EU Code of Conduct for Data Centres

• Singapore Standard SS 564: 2010

• ASHRAE TC9.9 2011 Thermal Guidelines for Data Centres

• EPA Energy Star Rating for Data Centres

• LEED / BREEAM

• PUE – Power Usage Effectiveness

• DCiE – Data Centre Infrastructure Efficiency

• WUE – Water Usage Effectiveness

• CUE – Carbon Usage Effectiveness

• TP-E/C/H – Transaction Processing

Coypright HP 2011 - Subject to Change Without Notice HP Confidential7 1 June 2011

PUE (Power Usage Effectiveness) DCiE (Data Centre infrastructure Efficiency) DCiE=1/PUE

Emergency generator

Utility transforme

r

Total data center power

(kw)

Data center power usage effectiveness (PUE)

Total data center power (kw)

Total IT power (kw)

Main

power

House

power

Misc.

power

IT

power In

Mech.

power

Total data center power

(kw)

House power (kw)

(+)=

(+) (+) =

=

Data center

Main service

PP-Gen service

Lighting panel

Generator block Heaters & lighting

Lighting, Exit lights, BMS, EPMS & security

House panels

UPS

STS

PDUs

RPPs

Mech. Swgear

Data centerCRAC units,

AHUs, Chillers & Dry coolers

Misc. support Mech. support

Power

To IT

IT-critical load


Data Centre Energy Efficiency Assessment

• Provides metrics of data centre facility’s energy efficiency

• Provides power efficiency benchmarking data of facility in comparison

with other facilities

• Determines the carbon footprint of your facility

• Identifies mechanical and electrical sources of inefficiency

• Identifies operational and maintenance practices that may affect

energy efficiency

• Provides understanding of mechanical and electrical best practices that

can increase energy efficiency

• Outlines mechanical and electrical concepts that may improve

efficiency with associated high-level cost-benefit analysis


EEA Preparation:

• Obtain MEP documents & Utility data

• Determine an approach to the Audit (Hi-Level or Detailed audit)

• Create EEA file with equipment according to drawings (enter all design data) at this stage

• Define test and measurement points for all equipment

EEA Execution:

• Site Visit and kick-off meeting/presentation

• Conduct initial walk-through & ensure as-built condition

• Collect Data from name plate/ manuals/BMS

• Prepare instrumentation & gather power/Temp measurements

• Analyse data

EEA Report:

• Perform detailed analysis and evaluation

• Analyse what if scenarios

• Insert additional data into the EEA tool if needed

• Formulate findings, observations and recommendations

• Report Output

Audit Preparation

1 week

Step-1

Audit Execution

1 week

Step-2

Audit Report

4 weeks

Step-3

6 WEEKS

Data Centre Energy Efficiency Assessment


PUE Results

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

Percent of Total Facility Power

Facility Number

ICT Load (%) Mechanical (%) Electrical Losses (%) Electrical and Lighting (%)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

Percent of Total Facility Power

Facility Number

ICT Load (%) Mechanical (%) Electrical Losses (%) Electrical and Lighting (%)

Average Singapore PUE = 2.39

DCiE = 0.42

©2009 HP Confidential11

Data Centre Benchmarking - Key Findings

•High Bypass and Recirculation

•Mixed aisle configurations

•No blanking panels/cable skirts

•No air management strategies

•Data centre too cold

•UPS rooms too cold

•Too many AC units/Turn some AC units off

•Controlled on return air

•Low air temp & %RH set points!

•Fixed speed fans, no VFDs

•Old fan motors with low efficiency

• No centralized communications

•Mixed up flow/down flow units

• Low chilled water set points

• No VFDs on pumps/CT fans

• Plant maintenance issues

• Plant age

• Chillers sequencing/staging

• Fixed speed chillers, no VFDs

• No free cooling

• No condenser water temp reset

• Low UPS loads “load factor”

• Plant efficiency, age

• Maintenance issues

• Lights ON all the time in data

centers

−No occupancy zoned LED lights

−More lights require more cooling


Typical Output

Saving energy reduces OPEX which increases the bottom line. Often the ROI is a

Matter of weeks or months rather than years:

Recommendations

Est. first cost or incremental cost increase

Est. annual elec. savings

(kWh)

Est. annual cost savings

(USD)

Simple payback (years)

Increase UPS room temperature setpoint – $101,376 $12,064 Immediate

Increase switchgear room temperature setpoint – $30,660 $3,649 Immediate

Reduce condenser water temperature setpoint (verify with chiller manufacturer) – $37,450 $4,457 Immediate

Increase CRAC return air set point and tolerance range – $51,500 $6,100 Immediate

Shut down 3 CRAC units – $109,620 $13,000 Immediate

Shut down 44 CRAC units – $1,599,600 $190,350 Immediate

Raise primary chilled water temperature setpoint – $198,000 $23,500 Immediate

Disable all individual CRAC infrared humidifiers and rely on centralized humidification in main AHUs – $525,600 $62,500 Immediate

Widen CRAC unit return air humidity deadband to meet ASHRAE standards $3,000 $158,000 $18,800 0.2

Add air side economizers to AHUs $24,000 $1,260,400 $150,000 0.2

Use liquid-cooled server cabinets in lieu of cabinets cooled by rejecting heat to data center (large DC) $85,000 $1,280,000 $128,000 0.7

Use chillers with variable speed compressors in lieu of constant speed compressors with solid state starter $300,000 $6,000,000 $360,000 0.8

Shut off 3 CRAC/H units $5,000 $62,500 $5,000 1.0

Fast ROI


Thermal Scans – Computer Racks

1 1 CF L O OROP E N I N G2 0 CS ER V ER SE X H A U ST

HOT AISLE SHORT CIRCUITING

FROM UNSEALED CABLE

CUTOUTS IN THE RAISED

FLOOR

H O TA I S L E

H O TA I S L EHOT AISLE SHORT CIRCUITING

FROM UNSEALED CABLE

CUTOUT DIRECTLY BELOW

EMPTY SERVER RACK

1 3 C A I RC O M I N G FR O MI N S I D E A NE M P T Y S ER V ERR A CK

2 0 CS ER V ER SE X H A U ST

©2009 HP Confidential1414 1 June 2011

Aisle ContainmentExample: Enclosed Hot Aisle Layout

• Air supplied from side walls down cold aisle

• Air is returned above drop ceiling

• Enclosed Hot Aisle

14

• Pros:

• Eliminates Bypass Airflow

• Eliminates Recirculation/ Hot Spots

• Allows Variable Supply Airflow to Match Server Airflow

• Lower Energy Cost

• Cons:

• First Cost of Enclosures

• Additional Lighting and Fire Protection Devices


Server Level

Consider cloud SaaS, IaaS, EaaS etc. There are huge opportunities for

Energy savings provided server utilization is high.


Need to look at entire life cycle to determine total energy and environmental impact

Includes material embodied energy and operating phase contributions

Techniques are not new, but data sets and standardized techniques are still emerging

Embedded Energy

Life Cycle Assessment Concepts

Analyzing total environmental foot print

General findings:

• The operational phase of a data center has the greatest impact to life cycle energy use and CO2 emissions

• Materials used in structural and HVAC systems are the two largest contributors when looking at embodied energy


Embedded Energy in a Data Centre


Air Management Objective: Increase air & chw set points- Minimise Negative flow and Bypass- Minimise Recirculation

Mechanical- Free Cooling (air or chw)- Plant / system optimise

- Chillers- CRACs- Humidifiers, etc

Electric performance- UPS- Gen heaters - Lights- dc power

Renewable power (mains /on-site)- Mains (wind, hydro)- Site (bio-fuel cogeneration)

Data Centre Energy & Sustainability Strategy

IT Server:(> Efficient)(> Utilisation)> T (& RH) range


Data Centre Facility - Trends

• Modular data halls & containers

• Various free cooling techniques

• Variable density

• Aisle Containment

• Higher Densities

• Gradually moving to Liquid Cooling

• Real time measurement of PUE/TP-E

• Move away from conventional ac power to dc power

• Variable reliability:-

• Multi-tiering

• Clustering HW/SW

• Network diversity

•Widening of acceptable server inlet thermal limits


End of Session

Using Data Centre Energy Benchmarking to Enhance ... Ed Ansett_neeconf.pdf · • Polymer,...

Documents

Transcript of Using Data Centre Energy Benchmarking to Enhance ... Ed Ansett_neeconf.pdf · • Polymer,...