DC MASTER Boreas DCM As A High Efficient Cooling Solution For Data - - PowerPoint PPT Presentation

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DC MASTER Boreas DCM As A High Efficient Cooling Solution For Data - - PowerPoint PPT Presentation

Feb 27, 2024 396 likes •635 views

DC MASTER Boreas DCM As A High Efficient Cooling Solution For Data Centres BOREAS KLIMA Boreas Klima is established in Istanbul- Turkey as a member of ACIK Holding. All the engineers and technicians have many years of experience in

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SLIDE 1

DC MASTER

Boreas DCM As A High Efficient Cooling Solution For Data Centres

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SLIDE 2
  • Boreas Klima is established in Istanbul-

Turkey as a member of ACIK Holding.

  • All the engineers and technicians have

many years of experience in the design and manufacture of HVAC products.

BOREAS KLIMA

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SLIDE 3

As our digital addiction increases, the power we consume increases in parallel. By-product of the process is HEAT. This presentation introduces a reliable and energy-efficient method for data centers cooling.

Heat Loads In Data Centre

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SLIDE 4

ADIA-MECHANIC Cooling

Adia-Mechanic Cooling is a highly efficient way of data centres cooling.

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SLIDE 5

Working Principle

  • When outdoor

temperature is cold enough, outdoor air flow used to cool the indoor air cycle while two air flows do not mix. (Free Cooling)

  • On warm days, water

spraying to the outdoor air flow, increases cooling

  • effect. (Indirect Adiabatic

Cooling)

  • Mechanical cooling trims

the supply temperature on hot days.

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SLIDE 6

Adia-Mechanic Cooler

  • The unit uses air-to-air

heat exchanger for transferring data center’s heat with the

  • utdoor air stream.

Indoor Air Cycle Outdoor Air Stream

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SLIDE 7

Adia-Mechanic Cooler

  • The most economical

mode of operation is achieved by using Free Cooling, Indirect Evaporative Cooling and Mechanical Cooling alone or together.

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SLIDE 8

Why Adia-Mechanical Cooling Be Preferred

Advanced control algorithm ensures most efficient cooling methode, for reducing

  • perating cost.
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SLIDE 9
  • Free Cooling (DRY)
  • Adiabatic Cooling (WET)
  • Mechanical Cooling (DX)
  • Adiabatic + Mechanical Cooling

(WET+DX) Annual temperature hours (Istanbul as an example) shows savings potential. Most of the year the unit

  • perates with free cooling and

indirect adiabatic cooling modes.

Operating Modes

DRY 20 ͦC DB * 5 ͦC DB 57kJ/kg* DRY / WET WET/ WET+DX WET + DX

DRY

Free Cooling Only

DRY / WET

DRY/WET Cooling, Selected By Cost Control

WET/WET+DX

WET/WET+DX Cooling, Selected By Cost Control

WET + DX

WET + DX Cooling

* Set değeri 24 ͦC için

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SLIDE 10
  • Absolutely NO!
  • Fan motors consumes

energy while free cooling process.

  • More air flow required for

free cooling when outdoor temperature rises.

  • More air flow requires more

energy consumption.

Is Free Cooling Free As People Think?

DRY 20 ͦC DB * 5 ͦC DB 57kJ/kg* DRY / WET WET/ WET+DX WET + DX

* Set değeri 24 ͦC için

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SLIDE 11
  • pPUE is an indication of the

electrical energy consumption

  • Water is another material

consumed for the cooling

  • Operating cost is the sum of

electricity and water costs in currency units.

  • Operating the unit with cost

control can be more economical.

pPUE vs Operating Cost

DRY 20 ͦC DB * 5 ͦC DB 57kJ/kg* DRY / WET WET/ WET+DX WET + DX

* Set değeri 24 ͦC için

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SLIDE 12

N+1 Unit pPUE Calculation With ASHRAE London Data

Power Consump tion (kW) Total Energy Consumption (kWh) Water Evaporation (l/h) Total Water Consumption (m3)

  • 9,0
  • 9,3 0,160396

DRY 13049 44514

11,57 1,9 0,00 0,00

  • 8,0
  • 8,0 0,080285

DRY 13346 44514

11,58 0,9 0,00 0,00

  • 7,0
  • 7,4 0,680731

DRY 13587 44514

11,60 7,9 0,00 0,00

  • 6,0
  • 6,5 1,561365

DRY 13981 44514

11,62 18,1 0,00 0,00

  • 5,0
  • 5,5 4,364766

DRY 14322 44514

11,64 50,8 0,00 0,00

  • 4,0
  • 4,4 9,251909

DRY 14680 44514

11,66 107,9 0,00 0,00

  • 3,0
  • 3,7 17,78341

DRY 15057 44514

11,69 207,9 0,00 0,00

  • 2,0
  • 2,6 37,48063

DRY 15453 44514

11,72 439,3 0,00 0,00

  • 1,0
  • 1,7 62,22772

DRY 15871 44514

11,76 731,8 0,00 0,00

0,0

  • 0,8 98,93075

DRY 16312 44514

11,80 1167,4 0,00 0,00

1,0 0,1 160,2784 DRY 16778 44514

11,84 1897,7 0,00 0,00

2,0 1,0 203,8577 DRY 17271 44514

11,89 2423,9 0,00 0,00

3,0 1,9 246,3214 DRY 17795 44514

11,94 2941,1 0,00 0,00

4,0 2,8 294,59 DRY 18351 44514

12,01 3538,0 0,00 0,00

5,0 3,8 351,5816 DRY 18943 44514

12,08 4247,1 0,00 0,00

6,0 4,7 391,352 DRY 19574 44514

12,16 4758,8 0,00 0,00

7,0 5,6 444,1397 DRY 20250 44514

12,25 5440,7 0,00 0,00

8,0 6,5 492,7241 DRY 20973 44514

12,36 6090,1 0,00 0,00

9,0 7,4 538,7675 DRY 21817 44514

12,48 6723,8 0,00 0,00

10,0 8,3 543,3367 DRY 22787 44514

12,63 6862,3 0,00 0,00

11,0 9,2 544,9757 DRY 23864 44514

12,81 6981,1 0,00 0,00

12,0 10,0 532,18 DRY 25066 44514

13,01 6923,7 0,00 0,00

13,0 10,9 517,891 DRY 26423 44514

13,26 6867,2 0,00 0,00

14,0 11,7 482,2759 DRY 27970 44514

13,58 6549,3 0,00 0,00

15,0 12,5 470,8114 DRY 29759 44514

14,02 6600,8 0,00 0,00

16,0 13,2 450,4599 WET 27170 44514

14,21 6401,0 34,18 15,40

17,0 13,8 395,6819 WET 28136 44514

14,42 5705,7 40,95 16,20

18,0 14,2 331,0726 WET 28830 44514

14,59 4830,3 50,49 16,72

19,0 14,7 263,5764 WET 29759 44514

14,82 3906,2 59,40 15,66

20,0 15,0 217,6346 WET 30352 44514

14,98 3260,2 70,99 15,45

21,0 15,5 170,4084 WET 31413 44514

15,27 2602,1 81,06 13,81

22,0 16,0 133,2235 WET 32574 44514

15,62 2081,0 91,87 12,24

23,0 16,5 98,68029 WET 33850 44514

16,03 1581,8 103,54 10,22

24,0 16,8 74,41846 WET 34682 44514

16,26 1210,0 117,74 8,76

25,0 17,2 55,76413 WET 35880 44514

16,74 933,5 132,00 7,36

26,0 17,6 41,7532 WET 37195 44514

17,03 711,1 147,34 6,15

27,0 18,1 28,14617 WET 39037 44514

17,96 505,5 163,77 4,61

28,0 18,4 18,93875 WET 40268 44514

18,48 350,0 182,18 3,45

29,0 18,9 13,01372 WET 42586 44514

19,60 255,1 202,46 2,63

30,0 19,1 9,409966 WET 43620 44514

20,16 189,7 223,53 2,10

31,0 19,6 5,165772 WET + DX 31800 44514

22,36 115,5 170,33 0,88

32,0 19,9 2,482978 WET + DX 32700 44514

22,60 56,1 185,59 0,46

33,0 20,6 1,201784 WET + DX 35400 44514

23,45 28,2 203,96 0,25

34,0 20,7 0,681055 WET + DX 35800 44514

23,58 16,1 220,97 0,15

35,0 20,2 0,440681 WET + DX 33700 44514

22,87 10,1 232,43 0,10

36,0 19,5 0,160264 WET + DX 31600 44514

22,25 3,6 241,93 0,04

37,0 19,0 0,080128 WET + DX 30300 44514

21,90 1,8 252,04 0,02

Outdoor

  • Temp. (°C)

Wet Bulb

  • Temp. (°C)

ASHRAE Annual hours (h)

PRODUCT FOR 1000KW DATA HALL

Operation Mode Outdoor Airflow (m3/h) Cooling Airflow (m3/h)

1 Unit Energy Consumtion (kwH) / Year 116.334 1 Unit Water Consumtion (m3) / Year 153

  • Num. Of Active Units N+1

6

pPUE For 1MW IT Load With 6 Units 1,080

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SLIDE 13
  • Roof Top
  • Wall Connected
  • Dehumidifying
  • Humidifying

Alternatives

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SLIDE 14

Dehumidifying And Humidifying Processes

  • Dehumidification is carried
  • ut with the second cooling

cycle.

  • One main and one spare

unit in each hall has the feature of humidification and / or dehumidification.

  • Humidification is carried out

with a steam humidifier.

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SLIDE 15

Control System

  • In House Developed Unique

Control Algorithm Is The Most Important Compenent Of This System.

  • Algorithm controls the amount
  • f outside air to control the

supply temperature without fluctuation and with lower

  • perational costs.
  • Without PID, the unit can

calculate how much air flow should be for achiving the set supply temperature.

  • This allows him to quickly reach

the target and stay at a constant temperature.

ΔHCOOLING , TSET ,

Teamwork Parameters VRIABLE CoolingLoad Determines

Cooling Air Flow

OUTCOME

ΔHCOOLING , TSET , HODA., Teamwork

Parameters Air Flow Calculation

ODA Flow TSET , HODA., Teamwork

Parameters CF Analysis

Running Mode

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SLIDE 16

Control System

  • Teamwork; All units

belonging to a hall are associated with the «Ring Topology».

  • There is no way to loose

communication in the teamwork.

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SLIDE 17

Machine Learning For Prediction And Control

  • The temperature distribution

may not be homogeneous in the data room.

  • By knowing the effect of each

unit in the hall and controlling them accordingly, homogeneous temperature distribution can be achieved.

  • Doing this with machine

learning has been brought to the trial phase.

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SLIDE 18
  • The laboratory is located in the

Boreas production facility in Istanbul on an area of 300m2

  • Test System Components:
  • AHU Simulating Outdoor

Conditions

  • AHU Simulating Data Hall

Conditios

  • Chiller
  • Boilers
  • Scada System

Laboratory For FAT

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SLIDE 19
  • The system can carry out the

cooling capacity test up to 400 kW.

  • In summer or winter season;
  • + 15 C / + 40 C,
  • 70% / 30% RH

Conditions can be created

  • Return temperature of + 32C

/ + 40C can be provided to create DC conditions.

Laboratory For FAT

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SLIDE 20

Laboratory For FAT

  • During the tests, variables

such as temperature, humidity, air velocity, pressure, current, voltage and electrical power are measured from 41 points on the unit.

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SLIDE 21

Laboratory For FAT

  • The test operation can be

monitored on a large screen and a report can be printed

  • ut.
  • The trend lines can be

monitored for each parameter and the data recorded with a period of 10 s can be accessed at any time.

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SLIDE 22

THANK YOU