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Performance analysis and optimization of free cooling strategies for a liquid-cooled data center

  • Research Article
  • Building Systems and Components
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Abstract

The increasing power density of IT electronics and the enormous energy consumption of data centers lead to the urgent demand for efficient cooling technology. Due to its efficiency and safety, liquid-cooled heat sink technology may gradually replace air-cooled technology over time. With the ambient or higher water supply temperature, the liquid-cooled technology shortens the operating time of the chiller and improves its coefficient of performance, while the pump power consumption may increase for satisfying the constant cooling capacity. Therefore, it is significant to study the optimal water supply temperature to achieve energy-efficient operation of data centers. A virtual 30.1 kW data center is considered as the case, the liquid-cooled system is constructed with a combination of innovative manifold microchannel heat sink with oblique fins and indirect evaporative cooling technology to minimize energy consumption. A hybrid thermal management model integrating the heat dissipation model and the power consumption model is established by TRNSYS and FLUENT software. To the highest chip-safe operating temperature premise, the energy performance is analyzed under various water supply temperatures in Guangzhou. The result shows that only 21.5-hour mechanical cooling is needed with the 30 °C server inlet temperature throughout the year. And the minimized power consumption occurs with the constant 29 °C server inlet temperature. Moreover, the temperature adaptive control strategy (TACS) is adopted to test the cooling system power consumption under different regulation frequencies, and the by-week TACS can achieve another 11.5% energy saving than the minimum power consumption of the constant temperature control strategy.

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Abbreviations

c p :

specific heat capacity (J/(kg·K))

Nu :

Nusselt number

P :

power consumption (kW)

Q :

cooling load (kW)

q :

mass flow rate (kg/h)

q v :

volume flow rate (L/min)

ΔP :

pressure drop (Pa)

ΔT :

temperature difference (°C)

T :

temperature (°C)

ε :

wet bulb efficiency

CFD:

computational fluid dynamics

DC:

data center

HVAC:

heating, ventilation, and air conditioning

IEC:

indirect evaporative cooling

IECT:

indirect evaporative cooling tower

IT:

information technology

MAPC:

monthly average power consumption

MMHS-O:

manifold microchannel heat sink with oblique fins

PID:

proportion integral differential

PUE:

power usage effectiveness

TACS:

temperature adaptive control strategy

WSE:

water-side economizer

atm:

ambient air

ave:

average

c:

electronic chip

c1:

the first chip in series configuration

c2:

the second chip in series configuration

chill:

chilled water

cool:

cooling water

cws:

cooling water supply

d:

direct evaporation

i:

indirect evaporation

in:

inlet

max:

maximum

min:

minimum

out:

outlet

p:

primary air

s:

secondary air

wb:

wet bulb

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Acknowledgements

This study was financially supported under Guangzhou Science and Technology Plan Project (No. 202201010108), CAS Science and Technology Service Network Program Project (No. 20211600200082), and Guangzhou Development Zone International Science and Technology Cooperation Project Funding (No. 2021GH07).

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Authors and Affiliations

  1. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou, China

    Weinan Zhou, Qin Sun, Weimin Luo & Kaijun Dong

  2. University of Chinese Academy of Sciences, Beijing, China

    Weinan Zhou & Weimin Luo

  3. Guangdong Provincial Key Laboratory of New and Renewable Energy Research and Development, Guangzhou, China

    Weinan Zhou, Qin Sun & Kaijun Dong

  4. Guangdong Fushengda Intelligent Technology Co., Ltd., Dongguan, 523770, China

    Wei Xiao

  5. Guangzhou Goaland Energy Conservation Tech. Co., Ltd., Guangzhou, 510663, China

    Pengfei Cui

  6. School of Energy and Environment, City University of Hong Kong, Hong Kong, China

    Wei Wu

Authors
  1. Weinan Zhou
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  2. Qin Sun
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  3. Weimin Luo
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  4. Wei Xiao
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  7. Kaijun Dong
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Weinan Zhou, Qin Sun, Weimin Luo, Wei Xiao, Pengfei Cui, Wei Wu, and Kaijun Dong. The first draft of the manuscript was written by Weinan Zhou and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Qin Sun.

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Zhou, W., Sun, Q., Luo, W. et al. Performance analysis and optimization of free cooling strategies for a liquid-cooled data center. Build. Simul. 16, 1317–1330 (2023). https://doi.org/10.1007/s12273-023-1012-6

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  • DOI: https://doi.org/10.1007/s12273-023-1012-6

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