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Simulation of a temperature adaptive control strategy for an IWSE economizer in a data center

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  • Durand-Estebe, Baptiste
  • Le Bot, Cédric
  • Mancos, Jean Nicolas
  • Arquis, Eric

Abstract

Nowadays, with the constant evolution of Information Technology (IT) equipments, the energy consumption of data center over the world becomes a major concern. In 2011 the ASHRAE Technical committee 9.9 (TC9.9) issued important guidelines concerning server temperature and hygrometric environment to help engineer in the design of cooling solutions. While raising the temperature may be a source of heat pump energy savings, it induces an increase in the Computer Room Air Handling (CRAH) unit energy requirement, lowering the benefits. Hence optimal temperature cooling set point must be found to maximise the efficiency of the cooling plant. To test various chiller control strategy a “full scale” model is proposed. A 32kW data center is considered, cooled by a centrifugal heat pump linked to a wet cooling tower. An Integrated Water Side Economizer (IWSE) is added to minimize the energy consumption the regulation and the chilled air production is simulated with the software TRNSYS. The temperature field in the server room is calculated with the CFD code Thetis. To create a link between the 2 simulation environments, a Reduced Order Model (ROM) using Proper Orthogonal Decomposition (POD) is program with MATLAB. Finally this numerical model is used to investigate the effect of server room temperature increase on the cooling plant energy consumption. A new Temperature Adaptive Control Strategy (TACS) that minimizes the energy need is proposed and tested.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:134:y:2014:i:c:p:45-56
    DOI: 10.1016/j.apenergy.2014.07.072
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    References listed on IDEAS

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    2. Fan, Chengliang & Hinkelman, Kathryn & Fu, Yangyang & Zuo, Wangda & Huang, Sen & Shi, Chengnan & Mamaghani, Nasim & Faulkner, Cary & Zhou, Xiaoqing, 2021. "Open-source Modelica models for the control performance simulation of chiller plants with water-side economizer," Applied Energy, Elsevier, vol. 299(C).
    3. Heran Jing & Zhenhua Quan & Yaohua Zhao & Lincheng Wang & Ruyang Ren & Zichu Liu, 2020. "Thermal Performance and Energy Saving Analysis of Indoor Air–Water Heat Exchanger Based on Micro Heat Pipe Array for Data Center," Energies, MDPI, vol. 13(2), pages 1-24, January.
    4. 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.
    5. Borkowski, Mateusz & Piłat, Adam Krzysztof, 2022. "Customized data center cooling system operating at significant outdoor temperature fluctuations," Applied Energy, Elsevier, vol. 306(PB).
    6. 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.
    7. 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).
    8. 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.
    9. Shunling Ruan & Haiyan Xie & Song Jiang, 2017. "Integrated Proactive Control Model for Energy Efficiency Processes in Facilities Management: Applying Dynamic Exponential Smoothing Optimization," Sustainability, MDPI, vol. 9(9), pages 1-22, September.
    10. 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.
    11. 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.
    12. 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.
    13. Yuan, Xiaolei & Liang, Yumin & Hu, Xinyi & Xu, Yizhe & Chen, Yongbao & Kosonen, Risto, 2023. "Waste heat recoveries in data centers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    14. Pio Alessandro Lombardi & Kranthi Ranadheer Moreddy & André Naumann & Przemyslaw Komarnicki & Carmine Rodio & Sergio Bruno, 2019. "Data Centers as Active Multi-Energy Systems for Power Grid Decarbonization: A Technical and Economic Analysis," Energies, MDPI, vol. 12(21), pages 1-14, November.

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