HVAC system design to operational efficiency: Strategies and Metrics for improved Total Cost of Ownership

Transcription

1 HVA system design to operational efficiency: Strategies and Metrics for improved otal ost of Ownership Michel van Roozendaal Vice President Services and ontracting limate Solutions, urope, Middle ast Africa and ndia Datacenter Dynamics ondon 30 November 2011

2 Agenda Breaking down the Data enter nfrastructure ost Data enters and Surging Business Needs acility nfrastructure and nergy Usage Understanding the ull osts of Growth Uncovering the otal ost of Ownership Strategies and Metrics for mproved otal ost of Ownership wo Universal hallenges for Data enters Key Metrics for Data enter Performance Reliability Strategy for Unplanned Downtime fficiency Strategies to mprove PU nergy Management Strategy to sustain efficiency Delivering Solutions for Data enters - ase Studies hiller Plant Optimization fficiency mprovement ooling System Refresh 2 rane - Datacenter Dynamics, ondon - 30 November 2011

3 Agenda Breaking down the Data enter nfrastructure ost Data enters and Surging Business Needs acility nfrastructure and nergy Usage Understanding the ull osts of Growth Uncovering the otal ost of Ownership Strategies and Metrics for mproved otal ost of Ownership wo Universal hallenges for Data enters Key Metrics for Data enter Performance Reliability Strategy for Unplanned Downtime fficiency Strategies to mprove PU nergy Management Strategy to sustain efficiency Delivering Solutions for Data enters - ase Studies hiller Plant Optimization fficiency mprovement ooling System Refresh 3 rane - Datacenter Dynamics, ondon - 30 November 2011

4 Data enters and Surging Business Needs Breakdown of average costs at a typical company 40% Application Development 20% Development 20% Maintenance 100% otal osts 15% nd Users 15% Network 60% AN/ WAN 8% nfrastructure and acilities Operations 25% Data enter 17% Hardware, Storage 5% Other 4 rane - Datacenter Dynamics, ondon - 30 November 2011 Source: McKinsey & ompany Data enter accounts for ¼ of a typical corporate budget

5 acility nfrastructure and nergy Usage ooling Systems lectrical and Building Systems 50% 40% 10% % Sh hare otal lectrica al nergy Use quip. hiller Humidifier RA PDU UPS Switchgear/ Generator ighting 5 rane - Datacenter Dynamics, ondon - 30 November 2011 Source: Gartner nc, rane internal estimates ooling systems represent 40% of the energy bill

6 Understanding the ull osts of Growth missions from Data enters Worldwide (Mt O 2 ) 340 Volume servers ooling systems Power systems Mid-range servers Storage systems High-end servers 33% 17% 36% 6% 5% 3% 11% AGR 80 17% Source: SMAR 2020 Report, GeS (convened under UNP), he limate Group, McKinsey & ompany 2008 fficient cooling is one of the solutions to 20% emission reduction 6 rane - Datacenter Dynamics, ondon - 30 November 2011

7 Uncovering the otal ost of Ownership Hidden osts (80-90%) quipment/nstallation Maintenance osts nergy osts Operation costs Parts Repair costs fficiency issues onsumables HS issues Upgrades Performance Problems Shutdown osts Retrofit costs Visible osts (10-20%) Majority of life cycle costs occur post system installation 7 rane - Datacenter Dynamics, ondon - 30 November 2011

8 Agenda Breaking down the Data enter nfrastructure ost Data enters and Surging Business Needs acility nfrastructure and nergy Usage Understanding the ull osts of Growth Uncovering the otal ost of Ownership Strategies and Metrics for mproved otal ost of Ownership wo Universal hallenges for Data enters Key Metrics for Data enter Performance Reliability Strategy for Unplanned Downtime fficiency Strategies to mprove PU nergy Management Strategy to sustain efficiency Delivering Solutions for Data enters - ase Studies hiller Plant Optimization fficiency mprovement ooling System Refresh 8 rane - Datacenter Dynamics, ondon - 30 November 2011

9 wo Universal hallenges for Data enters Availability = Reliable Uptime and apex nergy fficiency = Opex and nvironment ooling impacts Uptime, Opex and nvironmental Goals 9 rane - Datacenter Dynamics, ondon - 30 November 2011

10 Key Metrics for Data enter Performance Reliability ier1 ier2 ier3 ier4 Representative site failure Annual planned downtime 6 failures/ 5 years 1 failure/ year 1 failure/ 2.5 years 1 failure/ 5 years 28.8 h 22 h 1.6 h 0.8 h System path Single path Single path Multiple path Multiple path Overall system No redundancy Redundancy Redundancy Redundancy redundancy (N) (N+1) (N+1) 2(N+1) fficiency Power Usage ffectiveness(pu) = acility Power / power Data center infrastructure efficiency(di) = power/ acility power*100 PU level Very nefficient Average fficient inefficient Di level 33% 40% 50% 67% 83% Very efficient R A B N 10 rane - Datacenter Dynamics, ondon - 30 November 2011

11 Reliability Strategy for Unplanned Downtime ooling systems account for 30% of data center downtime Annual unplanned downtime ier 1 ier 2 ier 3 ier 4 108min 90min 36min 18min Service Plan Regular maintenance xtend equipment lifecycle Site monitoring Reduce ailure Risk quipment status ritical alarm management Default of operation Predictive maintenance Alarm diagnosis vents mitigation ake corrective actions prior to downtime R A B N Proactive maintenance reduces failure rate by 30% 11 rane - Datacenter Dynamics, ondon - 30 November 2011 Source: Ponemon institute, MP O&M guide, RAN internal estimates

12 fficiency Strategies to mprove PU System Design and Operational Strategies 40 ondon recorded temperature Rapid restart JAN B MAR APR MA JUN JU AUG SP O NOV D Highest recorded temperature Average temperature ree ooling conomizer hilledwater redundancy mprove PU HVA optimization - no control nergy enhancement optimization pump hiller R A B N PU improvements can be achieved through design alternatives 12 rane - Datacenter Dynamics, ondon - 30 November 2011

13 System Design Strategy Minimize chiller use with ree ooling hilledwater redundancy conomizer HVA optimization ondon recorded temperature ree ooling mprove PU nergy enhancement JAN B MAR APR MA JUN JU AUG SP O NOV D Highest recorded temperature Average temperature R A B UPS 23 in room N 12 hiller plant efficiency improvement of 50 to 60% 13 rane - Datacenter Dynamics, ondon - 30 November 2011

14 System Design Strategy conomizer to minimize mechanical cooling conomizer hilledwater redundancy HVA optimization ree ooling mprove PU nergy enhancement xhaust Air Outside Air Return Air Supply Air R A B Specialized control N Achieve cooling efficiency improvement of 60 to 70% 14 rane - Datacenter Dynamics, ondon - 30 November 2011

15 System Design Strategy Replace UPS with chilled water redundancy hilledwater redundancy conomizer HVA optimization Server UPS Main power Power generator Server UPS Main power Power generator ree ooling mprove PU nergy enhancement hiller plant in operation Power failure hiller Plant UPS hiller plant in operation 30s UPS hiller plant in operation 2min Power generator start 15 rane - Datacenter Dynamics, ondon - 30 November 2011 Back up control hiller plant stop hiller plant stop Buffer tank pump ON Power failure Back up control ON 20s Power generator start 2min Pumpinterlock restart Reduce overall UPS power usage by 30% hiller plant restart hiller plant in operation 3-7min hiller plant atfull load R A B N

16 Operational Strategy Optimize hiller plant operation conomizer hilledwater redundancy HVA optimization ree ooling mprove PU nergy enhancement racer S hiller Plant ontrol UPS R A B N Save pump operation to improve chiller plant efficiency by 5-10% 16 rane - Datacenter Dynamics, ondon - 30 November 2011

17 Operational Strategy Adjust cooling to new server technology conomizer hilledwater redundancy HVA optimization ree ooling mprove PU nergy enhancement Data enter ear 1 Data enter ear 5-6 Upgraded Servers Optimize cooling system R A B Ambient 23 hilled water 12 Server acceptance: 23 Ambient 23 hilled water 12 Server acceptance 26 Ambient 26 hilled water 15 Server acceptance 26 N mprove chiller efficiency by 5% with no effect on RA 17 rane - Datacenter Dynamics, ondon - 30 November 2011

18 nergy Management Strategy nergy fficiency nhancement conomizer hilledwater redundancy HVA optimizatio n ompressor ree ooling mprove PU nergy enhancement luid xchanger hillers lose an estimated 1% efficiency per year Adiabatic cooling Automatic tube cleaning R A B N mprove Peak oad fficiency Avoid fficiency Degradation Achieve chiller efficiency improvement of 20-30% 18 rane - Datacenter Dynamics, ondon - 30 November 2011

19 mprove PU and Reduce osts umulative impact of efficiency strategies PU 2.00 nergy osts 5.2m ooling 40% of otal oad acility oad PU 1.76 ooling fficiency +32% (12.1) PU 1.72 ooling fficiency +7% (2.1) PU 1.71 ooling fficiency +2% PU 1.70 UPS savings +2% (0.7) (0.7) PU 1.68 ooling fficiency +3% (0.9) PU 1.68 ooling fficiency +46% 83.6 R A B 40 Baseline ree cooling Non hilled use water UPS Optimization Raise Adjust temp nhancement nergy otal mpact redundancy to Server nhancement PU level nefficient Average fficient 40% 50% 67% 83% Di level Source: RAN internal estimates N 40-50% gain on cooling system leads to 15-20% PU improvement 19 rane - Datacenter Dynamics, ondon - 30 November 2011

20 Operational Strategy to Sustain fficiency Building Management and nergy Analysis Gather energy usage data Data center nergy Data Data Storage Data available Operations cockpit fficiency(pu) follow-up Optimize facility performance Manage cooling requirements ear-over-ear Analysis Access real time information Manage energy use and costs against forecast (budgets) rack actual energy usage and costs vs. prior year Benchmark between buildings R A B N Measure and manage building energy consumption 20 rane - Datacenter Dynamics, ondon - 30 November 2011

21 Agenda Breaking down the Data enter nfrastructure ost Data enters and Surging Business Needs acility nfrastructure and nergy Usage Understanding the ull osts of Growth Uncovering the otal ost of Ownership Strategies and Metrics for mproved otal ost of Ownership wo Universal hallenges for Data enters Key Metrics for Data enter Performance Reliability Strategy for Unplanned Downtime fficiency Strategies to mprove PU nergy Management Strategy to sustain efficiency Delivering Solutions for Data enters - ase Studies hiller Plant Optimization fficiency mprovement ooling System Refresh 21 rane - Datacenter Dynamics, ondon - 30 November 2011

22 hiller Plant Optimization ONX & HANGS taly s biggest banking group m² over 2 buildings 2 chiller plants for a total of 7500 kw ooling systems 6 to 10 years old nergy cost for the two buildings about 2millions / year Manual reporting and analysis - no real business insight

23 hiller Plant Optimization Benefits New hiller plant strategy Building management system Operate chiller plant at optimum efficiency Monitor chiller plant operation Drill down into Key Performance ndicators (KP) Operate fewer chillers to deliver the same capacity: Higher reliability (more redundancy) Higher performance nergy enhancement program hiller plant operation follow up Maintain efficiency level Benefits Annual nergy saving = 10% Utility cost reduction = /year Week 1 after commissioning ooling plant consumption before and after Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 23 rane - Datacenter Dynamics, ondon - 30 November 2011

24 fficiency mprovement ONX & HANGS arrier-neutral data center in oulon, rance hiller plant with 2 * 500 kw chiller Standard efficiency equipment PU = inefficient xisting Building management system Added free cooling operation High energy saving potential (even in south of rance) thanks to high chilled water production (12 ) 3500 hours of free cooling operation at less than 14 ambient omplete installation (HVA, electrical wiring & panel, control update) 24 rane - Datacenter Dynamics, ondon - 30 November 2011

25 fficiency mprovement Benefits New hiller plant strategy Dry cooler for free cooling operation apacity ambient Operating hours: 3500 hours ntermediate heat exchanger (avoid glycol into the building) Piping installation lectrical connection ntegration and update to existing BMS Benefits ncreased efficiency hiller plant = 4.12 (+ 33%) Operating cost reduction /year (-26%) ncreased redundancy 2 chillers + free cooling PU improvement from inefficient to average 25 rane - Datacenter Dynamics, ondon - 30 November 2011

26 ooling System Refresh ONX & HANGS eading uropean provider of carrier-neutral data centers, standalone data center in Netherlands 1200 m² raised floor 1.8 MW cooling capacity with 3 water cooled chillers and 6 dry coolers xisting building management system Data center short of cooling capacity due to 32 d esign ooling system replacement mplemented free cooling onsidered higher ambient temperature of 35 Upgraded Building Management System Reliability and energy enhancement contract 26 rane - Datacenter Dynamics, ondon - 30 November 2011

27 ooling System Refresh Benefits New hiller plant strategy fficiency improvement 3 Water cooled chillers 5 high efficiency dry coolers (NW) Building Management System to optimize chiller plant performance nergy enhancement contract Reliability enhancement ontrol system redundancy Maintenance contract Benefits Reduced chiller plant power consumption by 50% Operating cost reduction Savings /year Dry oolers in room rane - Datacenter Dynamics, ondon - 30 November 2011

28 wo Universal hallenges for Data enters Availability = Reliable Uptime and apex nergy fficiency = Opex and nvironment our mission - Realized 28 rane - Datacenter Dynamics, ondon - 30 November 2011

29 hank you Michel van Roozendaal Vice President ngersoll Rand limate Solutions urope, Middle ast, ndia and Africa Michel_vanRoozendaal@irco.com Visit our booth for more information 29 rane - Datacenter Dynamics, ondon - 30 November 2011