Cooling on Demand - scalable and smart cooling solutions. Marcus Edwards B.Sc.

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1 Cooling on Demand - scalable and smart cooling solutions Marcus Edwards B.Sc. Schroff UK Limited

2 Data Centre cooling what a waste of money! A 1MW data center needs 177,000,000 kwh in its lifetime of 10 years Each data center (MW) produces the CO2 emission of cars About 2% of the worldwide CO2 emission is caused by the industrial IT. That is as much as the air traffic produce Worldwide power costs of data centers amounts approximately 6.4 billion Source: SearchDataCenter, DataCenter Kompendium 2009

3 Where to start? The Green Grid -PUE & DCiE PUE and DCiE are measurements that help to easily understand how power efficient a Data Center is. PUE Power Usage Effectiveness Total Utility Power / IT Power (lower the number the better). DCiE Data Center infrastructure Efficiency IT Power / Total Utility Power (higher the XX% the more efficient). Continuously measurement is necessary! (Value varies between day/night and time of year)

4 The Green Grid -PUE & DCiE

5 Cooling a key function and a major challenge Thermal lfailure is root cause for 55% of all equipment failures Data Center reliability & availability Maximize Equipment Life Smaller system footprint with increasing processing power Packing density per rack increases Source: Uptime Institute

6 Cooling a key function and a major challenge Energy for cooling greater than 25% of datacenter s overall energy consumption and growing Decrease cost of operation Power Costs Improve PUE / DCiE Source: Uptime Institute

7 Power Equals Heat Power In = Heat Out The best way to measure the amount of heat produced in a cabinet is to measure the power being consumed. Power = Voltage x Current = Watts Power wants to change back to heat! Every Watt of power nearly equals every Watt of heat produced increased server usage and new server generations = increased power usage = increased heat output = increasing cooling demand

8 Calculating Heat Load Do Not Use name plate power ratings to calculate heat load! This number is the amount of power possible by the power supply and is not directly associated with typical power usage! Power supplies are always over rated and over designed for the equipment they power! Use 50% to 75% as a basic starting point The best way to monitor heat load is by measuring the current Watts = Voltage x Current (Amps) You can only manage, what you measure! Option: IP addressable PDUs (Also monitoring of redundancies and line load)

9 Cooling capacity is oversized Check maximum available power at the DC location, this will finally limit your DC expansion Heat load has to be planed as accurate as possible by designing the DC. Oversized cooling capacities leads to inefficiency At the beginning a new build DC is usually only equipped with 20% to 30% of the IT-load it has been designed for Permanent monitoring of redundancies and cooling capacity Cooling has to be aligned with server (electronics) Leasing time for a server, app. 2-3 years new server generation Server utilization varies over the day Scalable and intelligent cooling systems are key!

10 First step - Air Management

11 Avoid mixing i of cold and Close open U s in the cabinet exhausted air! Close open areas besides the 19 area 19 blanking panel low cost, high h impact bl ki l blanking panel besides 19 area

12 Floor tiles Optimized floor tiles placement Perforated floor tiles only where necessary Use floor brushes Floor Brush Kits

13 Cable management Unstructured cabling leads to air resistance! If possible use overhead cabling trays Structured cabling in cabinets and raised floor

14 Hypothetical Data Center Cabinets in Hot Aisle / Cold Aisle configuration 40 Cabinets each with 10 kw IT load Base PUE 2.00 (Traditional non-optimized Data Center) Energy Costs 9p / kw hour Activity PUE Annual Annual Power Annual Power impact power (kw) Costs Savings Base non-optimized DC ,636, k - Blanking Panels ,565, k 6k Floor Brushes ,460, k 16k Optimized Floor Tile Placement ,285, k 31k Source: Hoffman CFM analysis

15 Cooling concepts Perforated cabinet doors Rear door cooler Integrated Liquid Heat exchanger Cold-aisle containment Hot-aisle containment

16 Perforated cabinet doors Cabinets in Hot Aisle / Cold Aisle configuration Panels and structured t cable management avoid mixing i of cold and exhausted air on rack level but not on room level Perforated doors should provide high perforation to support airflow Low initial investment (completely passive system) Low load capacity (up to 7kW) Additional costs for cooling! Cooling lost from CRAC to server Thermal gradient in front of the 19 area cost of operation Source: Hoffman

17 Additional hot spot cooling options Additional Fans Separation of cold and warm air No matter how much airflow volume a fan can never cool lower than the ambient temperature! Point of failure Rear door water cooling, the built-in water circuit efficiently removes the heat without raising the ambient temperature Separation of cold and warm air Limited to app. 15kW, cooling not adapted to server utilization Hot spot cooling with fans Rear door cooler

18 Chimney solutions Separation of cold and warm air / low investment Complex planning of arrangement To increase cooling capacity perforation of floor tiles play bigger role Location in the room is limited as air ducts Activity PUE impact Annual Annual Annual power Power Power Usage (kw) Costs Savings Base non-optimized DC ,636, k - CRAC Duct Work ,180, k 41k Source: Hoffman CFM analysis

19 Cold-aisle containment Total separation of hot and cold air. Overpressure in the contained aisle. - Output CRAC equal as temperature in front of the servers No thermal gradient in front of the 19 area inside the containment No over cooling, opportunity for temperature optimizations in the DC Higher load per cabinet with same climate control elements possible Low investment with short ROI; - No maintenance costs

20 Cold-aisle containment Activity PUE impact Annual power Usage (kw) Annual Power Costs Annual Power Savings Base non-optimized DC ,636, k - Containment Cold Aisle ,708, k 173k Source: Hoffman CFM analysis

21 Project Example Cold Aisle Containment Situation DC area 202m²; DC volume app. 600m³ 75 Server cabinets in 3 rows 5 CRAC with 32KW refrigerating capacity each All CRACs run under full load Delta temperature cabinet bottom/up up to 10 C Activity Optimized airflow in raised floor Optimized airflow inside the cabinet (Cable management, separation of cold and hot areas, closing of cable ducting) Prevent mixing of cold and hot air Cold Aisle Containment

22 Project Example Cold Aisle Containment Impact Delta t of 10 C minimized to 1.5 C Room temperature declined about 3-4 C As the cooling of the server improved the room temperature declined as well by 1-2 C Pressure inside the aisle almost no delta between CRAC output and inside aisle Additional activities to improve PUE: Over pressure: Reduction of CRAC fan speed Cold area: Rising the temperature from egg. 17 C to 23 C Warm area: Rising the temperature from egg. 22 C to C In this project one CRAC was shut down. The fan speed of the other CRACs was reduced by 50% Savings of 30% energy is possible!

23 Integrated Liquid Heat EXchanger Self contained cabinet fully sealed cabinet with child water heat exchanger Cooling power up to 40 kw Air and Water as heat carriers Quantity of energy a material can transport = Density of the material x Specific heat capacity of the material x Volume flow rate x Temperature difference Different materials offer different values for density and heat capacity. Moving from air to water increases density by nearly 4000 times. The only variable is the volume flow rate.

24 Integrated Liquid Heat EXchanger Separation of hot and cold air closed loop Location in the room CRAC independent, d no raised floor needed d Cooling is close to the heat Small footprint Self controlled by heat load (set air temperature) IP addressable, Web GUI and SNMP traps Activity PUE impact Annual power Usage (kw) Annual Power Costs Annual Power Savings Base non-optimized DC ,636, k - LHX Stand alone ,132, k 315k Source: Hoffman CFM analysis

25 Integrated Liquid Heat EXchanger Baying of cabinets as a closed loop system Designing a n+1 redundancy Side by side Redundancy via side by side

26 In Row Cooling - Cold Aisle Containment Additional in row chiller stand alone or Additional in row chiller stand alone or supporting CRAC

27 In Row Cooling - Hot-aisle containment Raised floors and space air conditioning are Raised floors and space air conditioning are surplus to requirements

28 In Row Cooling Combination of containment and water cooling Activity PUE impact Annual Annual Annual power Power Power Usage (kw) Costs Savings Base non-optimized i DC ,636, k - In Row Cooling ,256, k 394k Source: Hoffman CFM analysis

29 Summary PUE can be improved even with small investments. Containment is a must Integrated Liquid Heat Exchanger as a room independent solution cooling high density computing. Combination of containment and water cooling is most efficient Intelligent and scalable self controlled by heat load no over cooling cabinets can be prepared for additional units