IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v160y2020icp99-111.html
   My bibliography  Save this article

Study on influence of operating parameters of data center air conditioning system based on the concept of on-demand cooling

Author

Listed:
  • Han, Zongwei
  • Wei, Haotian
  • Sun, Xiaoqing
  • Bai, Chenguang
  • Xue, Da
  • Li, Xiuming

Abstract

To improve energy efficiency of data centers, an air conditioning system for the concept of demand-based on cooling was proposed. This system combines a heat pipe cooling cycle and a vapor compression cooling cycle. Besides, the evaporative condenser is used to further utilize the natural cooling source, and the evaporator is put into the rack to realize on-demand cooling. A mathematical model was established to perform simulations of the system. The results showed that the energy consumption of compressor and pump reduce with the rising of outdoor unit air flow and evaporator inlet temperature. The coefficient of performance (COP) was selected as a reference index. When the cooling capacity is 8000 W, 6400 W and 4800 W, the optimal outdoor unit air flow of the heat pipe mode is 2000 m3/h, 1400 m3/h and 800 m3/h, respectively, and that of the vapor compression mode is 4000 m3/h, 3600 m3/h and 2400 m3/h, respectively. With the rising of evaporator inlet temperature from 29 °C to 41 °C under rated conditions, the heat pipe mode COP increased by 30.11%, 13.52% and 6.30%, respectively, and the vapor compression mode COP increased by 74.65%, 82.12% and 90.97%, respectively.

Suggested Citation

  • Han, Zongwei & Wei, Haotian & Sun, Xiaoqing & Bai, Chenguang & Xue, Da & Li, Xiuming, 2020. "Study on influence of operating parameters of data center air conditioning system based on the concept of on-demand cooling," Renewable Energy, Elsevier, vol. 160(C), pages 99-111.
    • Handle: RePEc:eee:renene:v:160:y:2020:i:c:p:99-111
    DOI: 10.1016/j.renene.2020.06.100
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096014812031017X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.06.100?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Durand-Estebe, Baptiste & Le Bot, Cédric & Mancos, Jean Nicolas & Arquis, Eric, 2014. "Simulation of a temperature adaptive control strategy for an IWSE economizer in a data center," Applied Energy, Elsevier, vol. 134(C), pages 45-56.
    2. Han, Zongwei & Zhang, Yanqing & Meng, Xin & Liu, Qiankun & Li, Weiliang & Han, Yu & Zhang, Yanhong, 2016. "Simulation study on the operating characteristics of the heat pipe for combined evaporative cooling of computer room air-conditioning system," Energy, Elsevier, vol. 98(C), pages 15-25.
    3. Zhang, Penglei & Wang, Baolong & Wu, Wei & Shi, Wenxing & Li, Xianting, 2015. "Heat recovery from Internet data centers for space heating based on an integrated air conditioner with thermosyphon," Renewable Energy, Elsevier, vol. 80(C), pages 396-406.
    4. Witte, Henk J.L., 2013. "Error analysis of thermal response tests," Applied Energy, Elsevier, vol. 109(C), pages 302-311.
    5. Jouhara, Hussam & Meskimmon, Richard, 2014. "Heat pipe based thermal management systems for energy-efficient data centres," Energy, Elsevier, vol. 77(C), pages 265-270.
    6. Moazamigoodarzi, Hosein & Gupta, Rohit & Pal, Souvik & Tsai, Peiying Jennifer & Ghosh, Suvojit & Puri, Ishwar K., 2020. "Modeling temperature distribution and power consumption in IT server enclosures with row-based cooling architectures," Applied Energy, Elsevier, vol. 261(C).
    7. Chu, Wen-Xiao & Wang, Chi-Chuan, 2019. "A review on airflow management in data centers," Applied Energy, Elsevier, vol. 240(C), pages 84-119.
    8. Sorrentino, Marco & Acconcia, Matteo & Panagrosso, Davide & Trifirò, Alena, 2016. "Model-based energy monitoring and diagnosis of telecommunication cooling systems," Energy, Elsevier, vol. 116(P1), pages 761-772.
    9. Ham, Sang-Woo & Kim, Min-Hwi & Choi, Byung-Nam & Jeong, Jae-Weon, 2015. "Energy saving potential of various air-side economizers in a modular data center," Applied Energy, Elsevier, vol. 138(C), pages 258-275.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Selorm Kwaku Anka & Nicholas Lamptey Boafo & Kwesi Mensah & Samuel Boahen & Kwang Ho Lee & Jong Min Choi, 2022. "Study on the Performance of a Newly Designed Cooling System Utilizing Dam Water for Internet Data Centers," Energies, MDPI, vol. 15(24), pages 1-19, December.
    2. Han, Zongwei & Xue, Da & Wei, Haotian & Ji, Qiang & Sun, Xiaoqing & Li, Xiuming, 2021. "Study on operation strategy of evaporative cooling composite air conditioning system in data center," Renewable Energy, Elsevier, vol. 177(C), pages 1147-1160.
    3. Sermsuk, Maytungkorn & Sukjai, Yanin & Wiboonrat, Montri & Kiatkittipong, Kunlanan, 2022. "Feasibility study of a combined system of electricity generation and cooling from liquefied natural gas to reduce the electricity cost of data centres," Energy, Elsevier, vol. 254(PA).
    4. Heran Jing & Zhenhua Quan & Yaohua Zhao & Lincheng Wang & Ruyang Ren & Ruixue Dong & Yuting Wu, 2022. "Experimental Investigation of Heat Transfer and Flow Characteristics of Split Natural Cooling System for Data Center Based on Micro Heat Pipe Array," Energies, MDPI, vol. 15(12), pages 1-22, June.
    5. Han, Ouzhu & Ding, Tao & Zhang, Xiaosheng & Mu, Chenggang & He, Xinran & Zhang, Hongji & Jia, Wenhao & Ma, Zhoujun, 2023. "A shared energy storage business model for data center clusters considering renewable energy uncertainties," Renewable Energy, Elsevier, vol. 202(C), pages 1273-1290.
    6. Sun, Xiaoqing & Zhang, Ce & Han, Zongwei & Dong, Jiaxiang & Zhang, Yiqi & Li, Mengyi & Li, Xiuming & Wang, Qinghai & Wen, Zhenwu & Zheng, Baoli, 2023. "Experimental study on a novel pump-driven heat pipe/vapor compression system for rack-level cooling of data centers," Energy, Elsevier, vol. 274(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaofei Huang & Junwei Yan & Xuan Zhou & Yixin Wu & Shichen Hu, 2023. "Cooling Technologies for Internet Data Center in China: Principle, Energy Efficiency, and Applications," Energies, MDPI, vol. 16(20), pages 1-31, October.
    2. Vesterlund, Mattias & Borisová, Stanislava & Emilsson, Ellinor, 2024. "Data center excess heat for mealworm farming, an applied analysis for sustainable protein production," Applied Energy, Elsevier, vol. 353(PA).
    3. Cristina Ramos Cáceres & Suzanna Törnroth & Mattias Vesterlund & Andreas Johansson & Marcus Sandberg, 2022. "Data-Center Farming: Exploring the Potential of Industrial Symbiosis in a Subarctic Region," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    4. Borkowski, Mateusz & Piłat, Adam Krzysztof, 2022. "Customized data center cooling system operating at significant outdoor temperature fluctuations," Applied Energy, Elsevier, vol. 306(PB).
    5. Cho, Jinkyun & Kim, Yundeok, 2016. "Improving energy efficiency of dedicated cooling system and its contribution towards meeting an energy-optimized data center," Applied Energy, Elsevier, vol. 165(C), pages 967-982.
    6. Du, Yahui & Zhou, Zhihua & Yang, Xiaochen & Yang, Xueqing & Wang, Cheng & Liu, Junwei & Yuan, Jianjuan, 2023. "Dynamic thermal environment management technologies for data center: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    7. Isazadeh, Amin & Ziviani, Davide & Claridge, David E., 2023. "Global trends, performance metrics, and energy reduction measures in datacom facilities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    8. Shao, Shuangquan & Liu, Haichao & Zhang, Hainan & Tian, Changqing, 2019. "Experimental investigation on a loop thermosyphon with evaporative condenser for free cooling of data centers," Energy, Elsevier, vol. 185(C), pages 829-836.
    9. Hu, Zhi-Hua & Zheng, Yu-Xin & Wang, You-Gan, 2022. "Packing computing servers into the vessel of an underwater data center considering cooling efficiency," Applied Energy, Elsevier, vol. 314(C).
    10. Han, Zongwei & Ji, Qiang & Wei, Haotian & Xue, Da & Sun, Xiaoqing & Zhang, Xueping & Li, Xiuming, 2020. "Simulation study on performance of data center air-conditioning system with novel evaporative condenser," Energy, Elsevier, vol. 210(C).
    11. Habibi Khalaj, Ali & Scherer, Thomas & K. Halgamuge, Saman, 2016. "Energy, environmental and economical saving potential of data centers with various economizers across Australia," Applied Energy, Elsevier, vol. 183(C), pages 1528-1549.
    12. Naoki Futawatari & Yosuke Udagawa & Taro Mori & Hirofumi Hayama, 2020. "Impact of Fan Airflow of IT Equipment on Thermal Environment and Energy Consumption of a Data Center," Energies, MDPI, vol. 13(23), pages 1-27, November.
    13. Leehter Yao & Jin-Hao Huang, 2019. "Multi-Objective Optimization of Energy Saving Control for Air Conditioning System in Data Center," Energies, MDPI, vol. 12(8), pages 1-16, April.
    14. Zhang, Hainan & Shao, Shuangquan & Xu, Hongbo & Zou, Huiming & Tang, Mingsheng & Tian, Changqing, 2017. "Simulation on the performance and free cooling potential of the thermosyphon mode in an integrated system of mechanical refrigeration and thermosyphon," Applied Energy, Elsevier, vol. 185(P2), pages 1604-1612.
    15. Heran Jing & Zhenhua Quan & Yaohua Zhao & Lincheng Wang & Ruyang Ren & Ruixue Dong & Yuting Wu, 2022. "Experimental Investigation of Heat Transfer and Flow Characteristics of Split Natural Cooling System for Data Center Based on Micro Heat Pipe Array," Energies, MDPI, vol. 15(12), pages 1-22, June.
    16. Qiankun Chang & Yuanfeng Huang & Kaiyan Liu & Xin Xu & Yaohua Zhao & Song Pan, 2024. "Optimization Control Strategies and Evaluation Metrics of Cooling Systems in Data Centers: A Review," Sustainability, MDPI, vol. 16(16), pages 1-41, August.
    17. Manaserh, Yaman M. & Tradat, Mohammad I. & Bani-Hani, Dana & Alfallah, Aseel & Sammakia, Bahgat G. & Nemati, Kourosh & Seymour, Mark J., 2022. "Machine learning assisted development of IT equipment compact models for data centers energy planning," Applied Energy, Elsevier, vol. 305(C).
    18. He, Wei & Ding, Su & Zhang, Jifang & Pei, Chenchen & Zhang, Zhiheng & Wang, Yulin & Li, Hailong, 2021. "Performance optimization of server water cooling system based on minimum energy consumption analysis," Applied Energy, Elsevier, vol. 303(C).
    19. Aneta Sapińska-Sliwa & Marc A. Rosen & Andrzej Gonet & Joanna Kowalczyk & Tomasz Sliwa, 2019. "A New Method Based on Thermal Response Tests for Determining Effective Thermal Conductivity and Borehole Resistivity for Borehole Heat Exchangers," Energies, MDPI, vol. 12(6), pages 1-22, March.
    20. Lu, Tao & Lü, Xiaoshu & Välisuo, Petri & Zhang, Qunli & Clements-Croome, Derek, 2024. "Innovative approaches for deep decarbonization of data centers and building space heating networks: Modeling and comparison of novel waste heat recovery systems for liquid cooling systems," Applied Energy, Elsevier, vol. 357(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:160:y:2020:i:c:p:99-111. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.