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A generic design optimization framework for semiconductor cleanroom air-conditioning systems integrating heat recovery and free cooling for enhanced energy performance

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  • Zhao, Wenxuan
  • Li, Hangxin
  • Wang, Shengwei

Abstract

High-tech industrial buildings, such as semiconductor cleanrooms, generally require strict temperature, humidity, and cleanliness controls, resulting in very high energy consumption of their air-conditioning systems. However, there exist two important problems in these air-conditioning systems, i.e., large cold-heat offset and low cooling efficiency. These two serious issues are generally neglected during the design stage and further cause great energy waste during the operation stage. This study therefore proposes a generic air-conditioning system design optimization framework for semiconductor cleanrooms by integrating heat recovery and free cooling techniques at air-side and water-side, respectively. The proposed design framework can fully eliminate cold-heat offset, simultaneously reduce cooling/heating loads and enhance cooling efficiency under full-range semiconductor applications. By detailed modeling and simulations, the proposed design framework is validated and tested under various indoor cooling loads, ventilation rates, and surrounding weather and climate conditions. Results show that 2.3–33.1 % energy savings are achieved and up to 15.8GJ/m2 annual primary energy is saved, compared with the conventional design. It is also observed that cities in cold and mild climates have higher energy-saving potentials than those in hot climates. It is recommended to utilize the proposed design framework as a benchmarking air-conditioning system design in new semiconductor cleanrooms.

Suggested Citation

  • Zhao, Wenxuan & Li, Hangxin & Wang, Shengwei, 2024. "A generic design optimization framework for semiconductor cleanroom air-conditioning systems integrating heat recovery and free cooling for enhanced energy performance," Energy, Elsevier, vol. 286(C).
  • Handle: RePEc:eee:energy:v:286:y:2024:i:c:s0360544223029948
    DOI: 10.1016/j.energy.2023.129600
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    References listed on IDEAS

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    1. Zhang, Yingbo & Shan, Kui & Li, Xiuming & Li, Hangxin & Wang, Shengwei, 2023. "Research and Technologies for next-generation high-temperature data centers – State-of-the-arts and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
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    5. Lu, Yuehong & Wang, Shengwei & Yan, Chengchu & Huang, Zhijia, 2017. "Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties," Applied Energy, Elsevier, vol. 187(C), pages 62-71.
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    1. Yu, Azhi & Ye, Qing & Li, Jinlong & Li, Xinhao & Wang, Yao & Rui, Qingqing, 2024. "Economic, environmental, energy, exergy (4E) analysis and simulated annealing algorithm optimization of dividing-wall column-intensified heterogeneous azeotropic pressure-swing distillation process," Energy, Elsevier, vol. 296(C).

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