Eficienta energetica in Centre de Date


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Eficienta energetica in Centre de Date

  1. 1. Eficien ţ a energetic ă î n Centre de Date. C â t de "Green" poate deveni un Centru de Date dac ă sunt implementate tehnologiile potrivite? Understanding PUE Best practices for improving PUE Setting realistic expectations Eduard Bodor Data Center BDM Central Europe APC by Schneider Electric
  2. 2. Power Generation <ul><li>regenerative/alternative Sources </li></ul><ul><li>Wind </li></ul><ul><li>Water </li></ul><ul><li>Solar </li></ul><ul><li>Fuel Cell </li></ul><ul><li>… </li></ul><ul><li>fossile and other Sources </li></ul><ul><li>Coal </li></ul><ul><li>Gas </li></ul><ul><li>Nuclear </li></ul><ul><li>Waste </li></ul>Today and Tomorrow Yesterday and Today power plant private industry power plant solar, wind private industry The easiest way to produce green energy is to save existing energy
  3. 3. <ul><li>Google 1.12 </li></ul><ul><li>Microsoft “data lab” 1.24 </li></ul><ul><li>Microsoft Generation 4 data centers (PUE target) 1.12 </li></ul><ul><li>A veteran designer of large-scale 1.08 data centers 1.06 1.046 </li></ul>The PUE derby Lets see how they get there…. Source … PUE reported … Great- Lets do it! Typical data center Extreme PUE claims 1.046 ! 1.12 1.24 2.1
  4. 4. <ul><li>PUE is based on math It is “knowable” using reasonable methods and standardized guidelines </li></ul><ul><li>PUE comparisons are difficult </li></ul><ul><li>Valid PUE comparisons are critically dependent on common terminology and assumptions </li></ul>Five key PUE concepts <ul><li>Shared building systems should be included for a real PUE Often overlooked, these need to be fairly allocated to data center operations </li></ul><ul><li>Redundancy worsens PUE Redundancy of power and cooling systems (an availability choice you make) reduces PUE because of lowered load across the redundant devices </li></ul><ul><li>Your electric bill and efficiency (PUE) are not the same thing One can get better while the other gets worse, for legitimate design decisions you might make </li></ul>Compare “apples to apples” and don’t overlook hidden electrical losses 1 2 3 4 5 What are reasonable PUE expectations?
  5. 5. When comparing PUE, always make sure it’s “apples to apples” “ The devil is in the details” The simple story The WHOLE story PUE represents how much EXTRA power (“electrical losses”) you consume to power, cool, and and protect the IT load LOWER is better, 1 is perfect But to get you need to ask questions ... <ul><li>What is included? ( What’s IN, what’s OUT? ) </li></ul><ul><li>Annualized average or point-in-time snapshot? </li></ul><ul><li>At what % load? (PUE degrades at lower loading) </li></ul><ul><li>In what geographical location? (e.g., access to “free cooling”) </li></ul>PUE = Power Usage Effectiveness IT load power Total data center input power
  6. 6. PUE less than 1.10? Unrealistic for ordinary data centers in ordinary places with ordinary budgets <ul><li>Choice of geographic location (for free-cooling opportunities) </li></ul><ul><li>An extensive fault-tolerant system architecture (so equipment failure doesn’t matter) </li></ul><ul><li>Nonstandard servers (e.g., NEBS carrier grade) that are more tolerant of Spartan conditions </li></ul><ul><li>AND … </li></ul><ul><li>A very large budget to meet green initiatives ! </li></ul>These extreme strategies are rarely suitable or fundable for the typical enterprise data center Very large, purpose built examples may be closing in on impressive PUEs, but they have flexibility and resources you may not have: No UPS Little or no power redundancy “ Free cooling” only No air conditioning fans
  7. 7. Moving towards a standardized calculation <ul><li>Data center efficiency is an evolving issue and standards are not settled yet </li></ul><ul><li>PUE standards are under development by industry stakeholders </li></ul><ul><li>White Papers discuss ongoing efforts toward standardized calculation of PUE </li></ul>Standardized calculations ensure that you are comparing “apples to apples” #158 A Standard Method for Calculation of Data Center Efficiency The industry is making progress …
  8. 8. The big question: What’s in, what’s out? Cooling subsystems are sometimes forgotten in the PUE calculation Leaving these out will falsely improve PUE Shared building-wide system power must be prorated for the data center’s share of use Items often omitted from the PUE calculation Excerpted from Table 1 in APC White Paper 158 √ Well pumps √ Unit heaters √ Make-up air / fresh air system power √ Condensate pumps √ Air compressors √ Pipe freeze protection √ Water treatment √ Cooling tower basin heaters Not included? Physical infrastructure? IT load? In the PUE formula, is it part of … Data center subsystem
  9. 9. PUE vs. the electric bill Beware of “Cause and Effect “ Be careful of using PUE as your only metric APC White paper 118 efficiency effects of virtualization It may not tell the whole story ! APC White paper 138 efficiency effects of increased inlet temperature BETTER (lower) Because of higher efficiency of cooling system WORSE (higher) If increased server fan power exceeds cooling system savings Higher server inlet temperature WORSE (higher) Unless power and cooling are downsized to align with lower IT load * BETTER (lower ) Because of optimized use of server capacity Virtualization / consolidation PUE Electric bill Data center design uprade
  10. 10. How many meters? Cost/benefit tradeoff for data collection APC White Paper #161 - Allocating data center energy costs and carbon to IT users Cost / benefit critical point Metering for PUE has diminishing returns, but metering has other benefits PUE error System cost 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% server counts UPS power crude inventory detailed inventory classify servers audit subsystems meter key subsystems meter all subsystems meter all IT devices Measurement Error (%) $0 K $100 K $200 K $300 K $400 K $500 K $600 K Measurement Cost ($)
  11. 11. Web-enabled interface For easy integration with 3rd party web page through application programming interface (API) Subsystem energy losses Insight into energy losses and cost of subsystems, with details of which subsystem draws the greatest cost Energy efficiency calculation Current and historical PUE values based on the current IT load for a fact-based understanding of energy efficiency at the facility level Efficiency dashboard
  12. 12. Subsystem breakdown of energy cost Air-cooled chiller Chilled water pump CRAH Switchgear Primary auxiliaries Lighting Generator Critical power dist. Critical auxiliaries UPS Cost (USD)
  13. 13. Go Go to online “live” version of this tool tools.apc.com
  14. 14. 2008 2018 2013 4 3 2 1 PUE 1.5 1.4 1.3 of data centers data center AVERAGE of data centers BEST 10% Where are YOUR data centers today? WORST 10% 3.3 2.1 1.5 worst best average The average will get better The worst will get MUCH better A realistic PUE forecast 2010
  15. 15. Drivers of infrastructure efficiency gains Baseline: Average of existing installed base Goal: Reduce PUE from 2.13 to 1.39 How to get there: Upgrades to power and cooling infrastructure Cooling ECONOMIZERS Convert from ROOM COOLING to dynamic ROW/RACK cooling RIGHT-SIZING via modular power and cooling Higher UPS EFFICIENCY 415/240 V TRANSFORMERLESS power distribution (NAM) DYNAMIC CONTROL OF COOLING PLANT (VFD fans, pumps, chillers) 32% contribution .24 PUE reduction 16% contribution .12 PUE reduction 16% contribution .12 PUE reduction 16% contribution .12 PUE reduction 10% contribution .07 PUE reduction 10% contribution .07 PUE reduction 1.39 Total pie represents the overall PUE improvement that we are talking about Each piece is the relative PUE contribution of upgrades that could be made PUE 2.13
  16. 16. “Hybrid” strategy <ul><li>High-density pods </li></ul><ul><li>Low-cost pods </li></ul><ul><li>High-availability pods (i.e. supported by extra redundancy) </li></ul>Build out in increments (“pods”) targeted on your current IT priorities Example: 6000 sq ft data center
  17. 17. <ul><li>Understand PUE </li></ul><ul><ul><li>Claims of extremely low PUE are becoming more common, but many are based on incomplete data and most are not realistic for your data center </li></ul></ul><ul><ul><ul><li>Leverage on-line tools to do ROI on efficiency improvements </li></ul></ul></ul><ul><ul><li>What’s In and What’s Out can dramatically effect PUE – always “compare apples to apples” </li></ul></ul><ul><ul><li>PUE is not the only metric you should look at – don’t forget the electric bill ! </li></ul></ul><ul><li>Choose your PUE measurement strategy </li></ul><ul><ul><li>Manual vs. automated </li></ul></ul><ul><ul><li>Lower vs. higher accuracy </li></ul></ul><ul><ul><li>Subsystem breakdown </li></ul></ul><ul><li>Consider your options for PUE improvement </li></ul><ul><ul><li>Close-coupled row-based cooling </li></ul></ul><ul><ul><li>High-efficiency scalable power and cooling </li></ul></ul><ul><ul><li>Tools for efficiency analysis and capacity management </li></ul></ul><ul><ul><li>Scalable/modular growth </li></ul></ul><ul><ul><li>Hybrid density data centers </li></ul></ul>PUE hype vs. realistic expectations Checklist for joining the PUE conversation with confidence   
  18. 18. Questions? Post-event questions or comments about this presentation? DCSC@APC.com - The Data Center Science Center at APC by Schneider Electric © 2009 APC by Schneider Electric